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Biblioteca

MARC Lista (tabellare)
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
Autore Liu Songbin
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (156 pages)
Disciplina 006.37
Soggetto topico Visió per ordinador
Aprenentatge automàtic
Machine learning
ISBN 3-030-89180-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910513688503321
Liu Songbin  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
Autore Liu Songbin
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (156 pages)
Disciplina 006.37
Soggetto topico Visió per ordinador
Aprenentatge automàtic
Machine learning
Soggetto genere / forma Llibres electrònics
ISBN 3-030-89180-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996466555003316
Liu Songbin  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Accountable and Explainable Methods for Complex Reasoning over Text / / by Pepa Atanasova
Accountable and Explainable Methods for Complex Reasoning over Text / / by Pepa Atanasova
Autore Atanasova Pepa
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (208 pages)
Disciplina 006.31
Soggetto topico Natural language processing (Computer science)
Information storage and retrieval systems
Machine learning
Natural Language Processing (NLP)
Information Storage and Retrieval
Machine Learning
Aprenentatge automàtic
Tractament del llenguatge natural (Informàtica)
Sistemes d'informació
Soggetto genere / forma Llibres electrònics
ISBN 3-031-51518-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Executive Summary -- Part I: Accountability for Complex Reasoning Tasks over Text -- 2. Fact Checking with Insufficient Evidence -- 3. Generating Label Cohesive and Well-Formed Adversarial Claims -- Part II: Explainability for Complex Reasoning Tasks over Text -- 4. Generating Fact Checking Explanations -- 5. Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing -- 6. Multi-Hop Fact Checking of Political Claims -- Part III: Diagnostic Explainability Methods -- 7. A Diagnostic Study of Explainability Techniques for Text Classification -- 8. Diagnostics-Guided Explanation Generation -- 9. Recent Developments on Accountability and Explainability for Complex Reasoning Tasks.
Record Nr. UNINA-9910847589903321
Atanasova Pepa  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Computing, Machine Learning, Robotics and Internet Technologies : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya
Advanced Computing, Machine Learning, Robotics and Internet Technologies : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (302 pages)
Disciplina 004
Collana Communications in Computer and Information Science
Soggetto topico Artificial intelligence
Computer engineering
Computer networks
Machine learning
Application software
Artificial Intelligence
Computer Engineering and Networks
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència artificial
Enginyeria d'ordinadors
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-031-47221-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Comparative Analysis of Different Machine Learning Based Techniques For Crop Recommendation -- Arduino based Multipurpose Solar Powered Agricultural Robot capable of Ploughing, Seeding, and Monitoring Plant Health -- Galactic Simulation: Visual Perception of Anisotropic Dark Matter -- Protocol Anomaly Detection in IIoT -- Agricultural Informatics & ICT: The foundation, issues, challenges and possible solutions—A Policy work -- A Guava Leaf Disease Identification Application -- Text to Image Generation using Attentional Generative Adversarial Network -- Attention-CoviNet:A Deep-Learning Approach to Classify Covid-19 using Chest X-Rays -- A Deep Learning Framework for Violence Detection in Videos using Transfer Learning -- Multi-focus Image Fusion methods: A Review -- Generation of a New Trust Establishment Pattern to Prevent Flooding Attacks in MANET -- A Survey on Cache Memory and On-Chip Cache Architecture -- AuthenticatingSmartphone Users Continuously Even If the Smartphone Is in the User’s Pocket -- Comparative Analysis of Machine Learning Algorithms for COVID-19 Detection and Prediction -- Machine Learning Classifiers Explanations with Prototype Counterfactual -- A Systematic Study of Super-Resolution Generative Adversarial Networks: Review -- Stance Detection in Manipuri Editorial Article using CRF -- Deep Learning Based Software Vulnerability Detection in Code Snippets and Tag Questions using Convolutional Neural Networks -- A Comprehensive Study of the Performances of Imbalanced Data Learning Methods With Different Optimization Techniques -- Smart Parking System using Arduino and IR sensor -- QuMaDe: Quick Foreground Mask and Monocular Depth Data Generation -- Fine-grained Air Quality with Deep Air Learning -- Enhancing Melanoma Skin Cancer Detection with Machine Learning and Image Processing Techniques -- Image Processing Technique and SVM forEpizootic Ulcerative Syndrome Fish Image Classification.
Record Nr. UNINA-9910847587503321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Computing, Machine Learning, Robotics and Internet Technologies : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part I / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya
Advanced Computing, Machine Learning, Robotics and Internet Technologies : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part I / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (297 pages)
Disciplina 004
Collana Communications in Computer and Information Science
Soggetto topico Artificial intelligence
Computer engineering
Computer networks
Machine learning
Application software
Artificial Intelligence
Computer Engineering and Networks
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència artificial
Enginyeria d'ordinadors
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-031-47224-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto A Hybrid Framework for implementing Modified K-Means Clustering Algorithm for Hindi Word Sense Disambiguation .-Detection of Leaf Disease using Mask Region based Convolutional Neural Network -- An Improved Machine Learning approach for throughput prediction in the Next Generation Wireless Networks -- Protein Secondary Structure Prediction without Alignment using Graph Neural Network -- A Lexicon-Based Approach for Sentiment Analysis of Bodo Language -- An Osprey Optimization based Efficient Controlling of Nuclear Energy-Based Power System -- Fuzzy Association Rule Mining Techniques and Applications -- Brain Tumor Detection Using VGG-16 -- Deep Learning model for Fish Copiousness Detection to Maintain the Ecological Balance between Marine Food Resources and Fishermen -- A Study on Smart Contract Security Vulnerabilities -- GUI Based Study of Weather Prediction using Machine Learning Algorithms -- A Systematic Review on Latest Approaches of Automated Sleep Staging System using Machine Intelligence Techniques -- Network Security Threats Detection Methods based on Machine Learning Techniques -- Optimized Traffic Management in Software Defined Networking -- Information Extraction for Design of a Multi-Feature Hybrid Approach for Pronominal Anaphora Resolution in a Low Resource Language -- Signature-based Batch Auditing Verification in Cloud Resource Pool -- Genetic Algorithm based Anomaly Detection for Intrusion Detection -- Machine learning based Malware Identification And Classification in PDF: A Review paper -- A Survey on Lung Cancer Detection and Location from CT Scan using Image Segmentation and CNN -- Bi-directional Long Short-Term Memory with Gated Recurrent Unit Approach for Next Word Prediction in Bodo Language -- Authorship Attribution for Assamese Language Documents: Initial Results -- Load Balancing and Energy Efficient Routingin Software-Defined Networking -- Sentiment Analysis: Indian Languages Perspective. .
Record Nr. UNINA-9910847589803321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XII / / edited by De-Shuang Huang, Yijie Pan, Jiayang Guo
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XII / / edited by De-Shuang Huang, Yijie Pan, Jiayang Guo
Autore Huang De-Shuang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (536 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science
Soggetto topico Computational intelligence
Machine learning
Computer networks
Application software
Computational Intelligence
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència computacional
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 9789819756155
9789819756148
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part XII -- Intelligent Computing in Computer Vision -- A 6-DoF Grasping Network Using Feature Augmentation for Novel Domain Generalization -- 1 Introduction -- 2 Methodology -- 2.1 Gaussian Noise Mix -- 2.2 Resblock Module -- 2.3 Local Features Interpolation -- 3 Experiments -- 3.1 Comparison with the State-of-the-Art -- 3.2 Generalization Analysis of Novel Domain -- 3.3 Visualization -- 3.4 Ablation Study -- 3.5 Practical Evaluation -- 4 Conclusion -- References -- TC-YOLO: Enhanced Vehicle Detection Approach for Traffic Surveillance Cameras Based on YOLOv8 -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Network Structure -- 3.2 Deformable Convolution for Enhancing Spatial Deformation Adaptability -- 3.3 Global Attention is Used to Enhance Cross-Dimensional Interaction Features -- 3.4 An Enhanced Detecting Head -- 4 Experiments -- 4.1 Experimental Dataset -- 4.2 Experimental Environment and Configuration -- 4.3 Evaluation Metrics -- 4.4 Algorithm Comparison -- 4.5 Ablation Study -- 5 Conclusion -- References -- MineDet: A Real-Time Object Detection Framework Based Neural Architecture Search for Coal Mines -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection Based on NAS -- 2.2 Lightweight Model Design -- 3 Method -- 3.1 The Reparameterization Technique -- 3.2 Efficient Search Space -- 3.3 Search Algorithm -- 4 Experimental -- 4.1 Dataset and Implementation Details -- 4.2 Experimental Results -- 5 Conclusion -- References -- Multi-gait Synthesis Based on Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 2.1 Multi-gait Dataset -- 2.2 2D and 3D Convolution -- 2.3 Image Synthesis -- 2.4 Encoder and Decoder -- 2.5 Gait Recognition -- 3 Method -- 3.1 CNN Block -- 3.2 Encoder -- 3.3 Feature Merging -- 3.4 Decoder -- 3.5 Optimization Strategy -- 4 Experiment.
4.1 Datasets -- 4.2 Single Frame and Multi Frame -- 4.3 Gait Recognition and Similarity Comparison -- 5 Summary -- References -- Controlling Attention Map Better for Text-Guided Image Editing Diffusion Models -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Diffusion Models -- 3.2 Inversion Methods -- 3.3 Attention Control Methods -- 4 Methodology -- 4.1 Motivation -- 4.2 Integrate Attention Control -- 5 Experiments -- 5.1 Benchmark -- 5.2 Implementation Details -- 5.3 Results -- 5.4 Ablation Study -- 6 Conclusion and Future Work -- References -- Spatial Group and Cross-Channel Attention: Make Smaller Models More Effective, Focus on High-Level Semantic Features -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Spatial Group and Cross-Channel Attention -- 3.2 Visualization and Interpretation -- 4 Experiments on Image Classification -- 4.1 Implementation Details -- 4.2 Image Classification -- 4.3 Parameter Experiment -- 5 Conclusion -- References -- YOLO-BS: A Better Object Detection Model for Real-Time Driver Behavior Detection -- 1 Introduction -- 2 Method -- 2.1 EVITS Module -- 2.2 ASPPMP Module -- 3 Experiments -- 3.1 Implementation Details -- 3.2 Datasets -- 3.3 Experimental Results -- 4 Conclusion -- References -- Fusion Attention Graph Convolutional Network with Hyperskeleton for UAV Action Recognition -- 1 Introduction -- 2 Proposed FA-GCN Method -- 2.1 The Network Architecture -- 2.2 Spatiotemporal Channel Fusion Attention Mechanism -- 2.3 Hyperskeleton Features -- 2.4 Gaussian Center Enhanced Interpolation Strategy -- 3 Experiments -- 3.1 Datasets and Experimental Setup Details -- 3.2 Ablation Studies and Comparative Analysis -- 3.3 Comparison with the State-of-the-Art -- 4 Conclusion -- References -- Enhancing Adversarial Robustness for Deep Metric Learning via Attention-Aware Knowledge Guidance -- 1 Introduction.
2 Related Work -- 3 Proposed Method -- 3.1 Preliminaries -- 3.2 Adversarial Attention-Aware Knowledge Guidance -- 3.3 Benign Attention-Aware Knowledge Guidance -- 3.4 Optimization -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Detailed Robustness Evaluation -- 5 Ablation and Discussions -- 5.1 Loss Function -- 5.2 Training Interval -- 5.3 Weak Robustness Subnet Width -- 5.4 Attention-Aware Knowledge Guidance -- 6 Conclusion -- References -- IMFA-Stereo: Domain Generalized Stereo Matching via Iterative Multimodal Feature Aggregation Cost Volume -- 1 Introduction -- 2 Related Work -- 2.1 Cost Filtering-Based Methods -- 2.2 Iterative Methods -- 3 Method -- 3.1 Multi-scale Feature Extractor -- 3.2 Initial Disparity Estimation -- 3.3 Aggregated Cost Volume -- 3.4 ConvGRU-Based Updater -- 3.5 Loss Function -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Ablation Study -- 4.3 Comparisons with State-of-the-Art -- 4.4 Cross-Domain Generalization -- 5 Conclusion -- References -- Anomaly Behavior Detection in Crowd via Lightweight 3D Convolution -- 1 Introduction -- 2 Method -- 2.1 Overall Framework -- 2.2 Channel-Only Polarized Self-attention -- 2.3 3D Separable Convolution -- 2.4 Truncated Singular Value Decomposition -- 3 Experiments and Analysis -- 3.1 Experimental Datasets and Preparation -- 3.2 Evaluation on Hajjv2 -- 3.3 Ablation Study -- 3.4 Validation on Benchmarks -- 3.5 Parameter Comparison and Results -- 4 Conclusion -- References -- Generating Graph-Based Rules for Enhancing Logical Reasoning -- 1 Introduction -- 2 Related Work -- 2.1 GNNs on Knowledge Graphs -- 2.2 Logical Rule Mining -- 3 Preliminary -- 4 Method -- 4.1 Graph-Based Rule Generator (GRG) -- 4.2 Subgraph Reasoning Module (SRM) -- 4.3 Loss Function -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Comparisons with Other Approaches -- 5.3 Ablation Studies.
5.4 Hyperparamter Analysis -- 5.5 Visualization Experiments -- 6 Conclusions -- References -- YOLO-PR: Multi Pose Object Detection Method for Underground Coal Mine -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Backbone Network Incorporating EPA Modules -- 3.2 Neck Network Integrating RFB Modules -- 3.3 Loss Function Based on PioU V2 -- 4 Experiments -- 4.1 Datasets and Evaluation Indicators -- 4.2 Result Analysis and Ablation Experiment -- 5 Conclusion -- References -- DSMENet: A Road Segmentation Network Based on Dual-Branch Dynamic Snake Convolutional Encoding and Multi-modal Information Iterative Enhancement -- 1 Introduction -- 2 Method -- 2.1 Overall Architecture -- 3 Dynamic Snake Convolution -- 3.1 Multi-modal Feature Fusion Module -- 3.2 Multi-modal Information Iterative Enhancement Module -- 4 Experiment -- 4.1 Datasets and Experimental Setup -- 4.2 Comparative Experiments -- 4.3 Ablation Study -- 5 Conclusion -- References -- MPRNet: Multi-scale Pointwise Regression Network for Crowd Counting and Localization -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Overall Counting and Localization Workflow -- 3.2 Multi-Scale Feature Extractor -- 3.3 Regional Maximum Substitution -- 3.4 One-to-One Points Matching -- 3.5 Training Objective -- 4 Experiment -- 4.1 Datasets and Configurations -- 4.2 Evaluation Metrics and Results -- 4.3 Ablation Studies -- 5 Conclusion -- References -- Text-to-Image Generation with Multiscale Semantic Context-Aware Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Model Overview -- 3.2 Semantic Adaptive Affine Fusion -- 3.3 CrossBlock Context Aware Encoding -- 3.4 Objective Function -- 4 Experiment -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 4.3 Ablation Studies -- 5 Future Work -- 6 Conclusion -- References.
CHMF: Colorful Human Reconstruction Based on Mesh Features -- 1 Introduction -- 2 Related Work -- 2.1 3D Human Color Estimation -- 2.2 3D Object Features Extraction -- 3 Method -- 3.1 Color Features Extraction and Mapping -- 3.2 Structural Features Extraction and Color Features Repair -- 3.3 Shape Features Extraction and Transformation -- 3.4 Features Decoding and Loss Functions -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Qualitative and Quantitative Comparisons -- 4.3 Ablation Study -- 4.4 Limitations -- 5 Conclusion -- References -- Face Swapping via Reverse Contrastive Learning and Explicit Identity-Attribute Disentanglement -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Reverse Contrastive Learning -- 3.2 Information Disentanglement -- 3.3 Loss Functions -- 4 Experiments -- 4.1 Experience Details -- 4.2 Comparison with Other Methods -- 4.3 Analysis of RCLSwap -- 5 Conclusion -- References -- OSFENet: Object Spatiotemporal Feature Enhanced Network for Surgical Phase Recognition -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Surgical Tool Alignment -- 3.2 Spatial Feature Encoder -- 3.3 Object Spatial Feature Enhanced Module -- 3.4 Object Temporal Feature Enhanced Module -- 3.5 Fusion Module -- 3.6 Loss Function -- 4 Experiments -- 4.1 Dataset -- 4.2 Experimental Settings -- 4.3 Online Surgical Phase Recognition Results -- 4.4 Offline Surgical Phase Recognition Results -- 4.5 Ablation Study -- 4.6 Qualitative Analysis -- 5 Conclusion -- References -- A Reinforced Passage Interactive Retrieval Framework Incorporating Implicit Knowledge for KB-VQA -- 1 Introduction -- 2 Related Work -- 2.1 Retrieval-Based Visual Question Answering Method -- 2.2 Large-Scale Model-Based Visual Question Answering Method -- 3 Methods -- 3.1 Implicit Knowledge-Driven Explicit Knowledge Retrieval -- 3.2 Passage Self-interaction -- 3.3 Model Training.
3.4 Retriever-Reader Generation.
Record Nr. UNINA-9910878979503321
Huang De-Shuang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XI / / edited by De-Shuang Huang, Yijie Pan, Qinhu Zhang
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XI / / edited by De-Shuang Huang, Yijie Pan, Qinhu Zhang
Autore Huang De-Shuang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (513 pages)
Disciplina 006.3
Altri autori (Persone) PanYijie
ZhangQinhu
Collana Lecture Notes in Computer Science
Soggetto topico Computational intelligence
Machine learning
Computer networks
Application software
Computational Intelligence
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència computacional
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 981-9756-12-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part XI -- Intelligent Computing in Computer Vision -- Priority Intra-model Adaptation for Traffic Sign Detection and Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Priority Intra-model Adaptation -- 3.2 TSDR Models -- 3.3 TT100K-FineNet and GTSDB-FineNet -- 4 Experiment -- 4.1 Datasets -- 4.2 Evaluation Metrics and Implementation Details -- 4.3 Experimental Results -- 5 Discussion -- 6 Conclusion -- References -- Adaptive Swin Transformers for Few-Shot Cross-Domain Silent Face Liveness Detection -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Overview -- 3.2 Network Architecture -- 3.3 Feature-Wise Transformation -- 4 Experiment -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Cross-Domain Performance -- 4.4 Ablation Study -- 5 Conclusion -- References -- DSFormer: Leveraging Transformer with Cross-Modal Attention for Temporal Consistency in Low-Light Video Enhancement -- 1 Introduction -- 2 Related Work -- 2.1 Low-Light Video Enhancement -- 3 Method -- 3.1 DSFormer Architecture -- 3.2 Flow Cross-Attention (FCA) -- 3.3 Spatial-Channel Multi-head Self-Attention (SCMA) -- 3.4 Dual Path Feed-Forward Network (DPFN) -- 4 Experiment -- 4.1 Implementation Detail -- 4.2 Static Video Evaluation -- 4.3 Dynamic Video Evaluation -- 4.4 Ablation Study -- 5 Conclusion -- References -- Robot Control Using Hand Gestures of the Mexican Sign Language -- 1 Introduction -- 2 Proposed Method -- 2.1 Segmentation Techniques -- 2.2 Feature Extraction -- 2.3 Feature Selection -- 2.4 Classification Techniques -- 2.5 Dataset -- 3 Experimental Results -- 4 Control Robot Method -- 4.1 Movement Orders Selection and Implementation -- 5 Conclusions -- References -- Improved Channel-Wise Semantic Alignment for Few-Shot Object Detection -- 1 Introduction.
2 Related Work -- 3 Problem Definition -- 3.1 Few-Shot Object Detection -- 3.2 Channel Attention -- 4 Our Method -- 4.1 Feature Purification -- 4.2 Sparse Channel Relation Distillation -- 5 Experiments -- 5.1 Datasets -- 5.2 Implementation Details -- 5.3 Comparison with the State-of-the-Arts -- 5.4 Ablation Study -- 6 Conclusion -- References -- Adapting Depth Distribution for 3D Object Detection with a Two-Stage Training Paradigm -- 1 Introduction -- 2 Related Work -- 2.1 Camera-Only 3D Object Detection -- 2.2 Depth Estimation -- 3 Preliminary -- 3.1 3D Object Detection -- 3.2 Multi-View Depth Estimation -- 3.3 LSS-Based 3D Object Detection Framework -- 4 Method -- 4.1 Two-Stage Training Paradigm -- 4.2 Depth Distribution Adaption -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 Main Results -- 5.3 Ablation Study -- 5.4 Validation Test: The Impact of Depth Accuracy on Detection -- 6 Conclusion -- 6.1 Limitations -- References -- Domain Adaptive Object Detection with Dehazing Module -- 1 Introduction -- 2 Related Work -- 2.1 Image Dehazing -- 2.2 Object Detection -- 2.3 Domain Adaptive Object Detection -- 3 Methods -- 3.1 Network Overview -- 3.2 Dehazing Module -- 3.3 Domain Adaptation -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Experiment of Fog Removal Module -- 4.3 Experiment of DefogDA-FasterRCNN -- 5 Conclusions -- References -- Improving Dynamic 3D Gaussian Splatting from Monocular Videos with Object Motion Information -- 1 Introduction -- 2 Related Work -- 2.1 Dynamic Scene Reconstruction -- 2.2 Depth Estimation -- 3 Preliminary -- 3.1 Problem Definition -- 3.2 3D Gaussian Splatting -- 3.3 Deformation Field -- 4 Method -- 4.1 Overview -- 4.2 Motion Segmentation -- 4.3 Three-Stage Training Strategy -- 4.4 Synthetic View Augmentation -- 5 Experiment -- 5.1 Setting -- 5.2 Comparisons -- 5.3 Ablation Study -- 6 Conclusion -- References.
Segmentation and Quality Assessment of Continuous Fitness Movements Based on Vision -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 WaveOptiSeg -- 3.2 TimeTransMLP -- 4 Experiments -- 4.1 Squat-Score Dataset -- 4.2 Evaluation Metrics -- 4.3 Implementation Details -- 4.4 Performance Comparison -- 5 Conclusion -- References -- Diagonal-Angle-Foreground IoU Loss Function for Small Object Detection -- 1 Introduction -- 2 Related Work -- 2.1 IoU Series Loss Functions for Bounding Box Regression -- 2.2 Summary -- 3 DAFIoU Loss Function -- 3.1 Angle-Based Loss Term -- 3.2 Diagonal-Based Loss Term -- 3.3 Foreground-Based Loss Term -- 3.4 DAFIoU (Diagonal, Angle, and Foreground Loss Function) -- 4 Experimental Results -- 4.1 Simulated Experiment -- 4.2 Ablation Experiment -- 4.3 YOLOv8s on Visdrone2019 -- 4.4 YOLOv8s on SODA-D10 -- 4.5 Faster R-CNN on Visdrone2019 -- 4.6 Visualization of Detection Results -- 5 Conclusion -- References -- Enhancing Dense Object Counting in Occlusion with a Dual-Branch Network -- 1 Introduction -- 2 Related Works -- 2.1 Neural Networks for Counting -- 2.2 Optimization Method of Dense Object Counting -- 3 Bilateral Counting Network -- 3.1 Density Region Extraction -- 3.2 Multi-lateral Collaborative Counting Network -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiment Settings -- 4.3 Experiment Results -- 5 Analysis -- 5.1 Ablation Studies -- 6 Limitations -- 7 Conclusion -- References -- Street Block Classification Based on Urban Satellite Images -- 1 Introduction -- 2 Dataset Building and Reprocessing -- 2.1 Dataset Building -- 2.2 Preprocessing of Public Datasets -- 3 Our Network Architecture -- 3.1 Feature Extractor -- 3.2 Adaptive Pyramid Pooling -- 3.3 Classifier -- 4 Experiments -- 4.1 Overall Accuracy -- 4.2 F1 Score -- 5 Conclusion -- References.
SRCFT: A Correlation Filter Tracker with Siamese Super-Resolution Network and Sample Reliability Awareness for Thermal Infrared Target Tracking -- 1 Introduction -- 2 Methodology -- 2.1 Algorithm Overview -- 2.2 Siamese Super-Resolution Network -- 2.3 Sample Reliability Awareness -- 3 Experiment -- 3.1 Implementation Details -- 3.2 Performance Comparison with State-of-the-Arts -- 4 Conclusions -- References -- Traffic Sign Detection and Recognition Using Gradient Training with an Improved YOLO Network -- 1 Introduction -- 2 Tri-modal Gradient Based Dataset Processing -- 2.1 First Gradient Dataset -- 2.2 Second Gradient Dataset -- 2.3 Third Gradient Dataset -- 3 IYOLO-TS -- 4 Experiments and Results -- 5 Summary and Outlook -- References -- Neural Radiation Fields via Accelerated and High Quality Parallel for Novel View Synthesis -- 1 Introduction -- 2 Related Work -- 2.1 Novel View Synthesis -- 2.2 Neural Radiance Fields -- 2.3 NeRFs with Explicit Volumetric Representations -- 3 Background and Motivation -- 4 Method -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Evaluation on Quality and Efficiency -- 5.3 Training on Consumer Devices -- 5.4 Comparison of Ablation Experiments -- 6 Conclusion -- References -- IOCSegFormer: Enhancing Wheat Ears Counting in Field Conditions Through Augmented Local Features -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 The Architecture -- 3.2 Local Segmentation Branch -- 3.3 Loss Function -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Datasets -- 4.3 Data Preprocessing -- 4.4 Results and Analysis -- 4.5 Ablation Studies -- 4.6 Visualizations -- 5 Conclusion -- References -- Stroke-Based Few-Shot Chinese Character Style Transfer -- 1 Introduction -- 2 Method -- 2.1 Dataset -- 2.2 Overall Pipeline -- 2.3 Cross-attention Module -- 2.4 Loss Functions -- 3 Result and Discussions -- 3.1 Evaluation Metrics.
3.2 Generated Chinese Character Images Results -- 4 Conclusion -- References -- Computer Vision Drives the New Quality Productive Forces in Agriculture: A Method for Recognizing Farming Behavior on Edge Computing Devices -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Employee Detection -- 3.2 Behavior Classification -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Evaluation Metrics -- 4.4 Experimental Results -- 5 Conclusions and Future Works -- References -- PS-DeiT: A Part-Selection Based DeiT for Fine-Grained Classification -- 1 Introduction -- 2 Related Work -- 3 Part-Selection Based DeiT -- 3.1 DeiT Based Feature Extractor -- 3.2 Knowledge Distillation Model -- 3.3 Part Selection Module -- 3.4 Loss Function Design -- 4 Experimental Results and Analysis -- 4.1 Implementation Details -- 4.2 Performance Evaluation -- 4.3 Ablation Study -- 5 Conclusion -- References -- Text-Guided Multi-region Scene Image Editing Based on Diffusion Model -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Mask Dilation Based Object Editing -- 2.3 OutwardLPF Based Background Coordination -- 3 Experimental Evaluation -- 3.1 Implementation Details -- 3.2 Main Results -- 3.3 Ablation Study -- 3.4 Scene Iterative Editing -- 4 Conclusion -- References -- MFANet: Multi-feature Aggregation Network for Domain Generalized Stereo Matching -- 1 Introduction -- 2 Related Work -- 2.1 Deep Stereo Matching -- 2.2 Domain Generalization -- 3 Method -- 3.1 Network Architecture -- 3.2 Multi-scale Adaptive Semantic Feature Aggregation -- 3.3 Multi-scale Texture Feature Aggregation -- 3.4 Recurrent Hourglass Aggregation Network -- 3.5 Disparity Regression and Loss Function -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Ablation Studies -- 4.3 Comparison with State-of-the-Art -- 4.4 Cross-Domain Generalization -- 5 Conclusion.
References.
Record Nr. UNINA-9910878065803321
Huang De-Shuang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XIII / / edited by De-Shuang Huang, Wei Chen, Qinhu Zhang
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part XIII / / edited by De-Shuang Huang, Wei Chen, Qinhu Zhang
Autore Huang De-Shuang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (536 pages)
Disciplina 006.3
Altri autori (Persone) ChenWei
ZhangQinhu
Collana Lecture Notes in Computer Science
Soggetto topico Computational intelligence
Machine learning
Computer networks
Application software
Computational Intelligence
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència computacional
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 981-9756-18-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part XIII -- Knowledge Discovery and Data Mining -- LeadRec: Towards Personalized Sequential Recommendation via Guided Diffusion -- 1 Introduction -- 2 Related Work -- 2.1 Sequence Recommendation -- 2.2 Diffusion Model -- 3 Preliminary -- 3.1 Forward Process -- 3.2 Reverse Process -- 3.3 Optimization -- 4 Lead Diffusion Recommender Model -- 4.1 LeadRec -- 4.2 LeadRec Blocks -- 5 Experiments -- 5.1 Dataset and Evaluation Metrics -- 5.2 Baselines and Training Protocol -- 5.3 Main Results -- 5.4 Further Analysis -- 6 Conclusion and Limitations -- References -- Anomaly Detection Method for Multivariate Time Series Data Based on BLTranAD -- 1 Introduction -- 2 Related Work -- 3 Methods -- 4 Experiment -- 4.1 Baseline -- 4.2 Dataset -- 4.3 Data Preprocessing -- 4.4 Experimental Settings -- 4.5 Evaluation Indicators -- 4.6 Results -- 5 Conclusion -- References -- MANet: A Mining and Analysis Method of Air Pollutants Transmission Path Network -- 1 Introduction -- 2 Methods -- 2.1 Related Work -- 2.2 Framework -- 2.3 Select Valid Data -- 2.4 Single Source Diffusion Influence Factor -- 2.5 Causal Mechanism-Oriented Construction Method -- 3 Experiment and Characteristic Analysis -- 3.1 The Generation of Pollutant Transmission Path Network -- 3.2 Validation and Analysis -- 4 Conclusion -- References -- HRMNN: Heterogeneous Relationship Mined Graph Neural Network -- 1 Introduction -- 2 Methodology -- 2.1 Node Features Projection -- 2.2 Relational Graph Generator -- 2.3 Object-Level Aggregation -- 2.4 Relation-Level Aggregation -- 3 Experiment -- 3.1 Datasets -- 3.2 Baseline -- 3.3 Node Classification -- 3.4 Node Clustering -- 3.5 Link Prediction -- 3.6 Ablation Study -- 4 Conclusion -- References -- Knowledge Completion Method Based on Relational Embedding with GNN -- 1 Introduction.
2 Knowledge Completion Based on GNN -- 2.1 Knowledge Graph Construction -- 2.2 Relational Embedding -- 2.3 Graph Neural Network (GNN) -- 2.4 Analysis of Classic Models -- 3 Discussion -- 3.1 Feature Learning Capability -- 3.2 Adaptability -- 3.3 Interpretability -- 3.4 Effective Processing of Graph-Structured Data -- 4 Conclusion -- References -- An Influence Blocking Maximization Algorithm Based on Community Division in Social Networks -- 1 Introduction -- 2 Problem Definition -- 3 Method -- 3.1 Community Division Based on Negative Seeds -- 3.2 Community Merging -- 3.3 The Allocation Process of the Positive Seeds -- 3.4 Finding Positive Seeds in the Community -- 4 Experiments and Result -- 4.1 Experimental Setting -- 4.2 Experimental Results -- 5 Conclusion -- References -- Research on Feature Selection Methods Based on Feature Clustering and Information Theory -- 1 Introduction -- 2 AP-MSU Feature Selection Model -- 2.1 Introduction to Related Work -- 2.2 Modeling Algorithm -- 3 Empirical Analysis -- 3.1 Analysis of the Effect of De-redundancy on the Dichotomous Dataset -- 3.2 De-redundancy Effect of Multi-categorization Dataset -- 4 Conclusions -- References -- A Redundant Relation Reduced Bidirectional Extraction Framework Based on SpanBERT for Relational Triple Extraction -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 SpanBERT-Based Encoder -- 3.2 Sentence Relation Prediction -- 3.3 Bidirectional Tagging Based Entity Extraction -- 3.4 Biaffine Based Relation Extraction -- 3.5 Training Strategy and Share-Aware Learning Mechanism -- 4 Experiment -- 4.1 Experiment Settings -- 4.2 Experiment Results -- 5 Conclusions -- References -- FEEL: A Framework for Evaluating Emotional Support Capability with Large Language Models -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Task Definition.
3.2 ESCEval: A Dataset of Human ESC Evaluation -- 3.3 Proposed FEEL -- 4 Experiments and Results -- 4.1 Implementation of FEEL -- 4.2 Comparative Results -- 4.3 Ablation Experiment -- 5 Conclusion -- References -- BACP: Bayesian Augmented CP Factorization for Traffic Data Imputation -- 1 Introduction -- 2 Preliminaries -- 3 Proposed Model: BACP -- 3.1 Model Analysis -- 3.2 Variational Inference of BACP -- 3.3 Algorithm Analysis -- 4 Experiments -- 4.1 Settings -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Improving Zero-Shot Stance Detection by Infusing Knowledge from Large Language Models -- 1 Introduction -- 2 Related Work -- 2.1 Zero-Shot Stance Detection -- 2.2 Data Augmentation Based on LLMs -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 LLM Knowledge Generation -- 3.3 Topic-Iterative Data Augmentation -- 3.4 Knowledge Infusion -- 4 Experiments -- 4.1 Datasets and Metrics -- 4.2 Implementation Details -- 5 Results and Analysis -- 5.1 Comparison Results -- 5.2 Ablation Results -- 5.3 Case Study -- 6 Conclusion -- References -- Robust Cyberbullying Detection in Diverse Textual Noise -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Attention-Based Compositional Embedding -- 3.2 Capsule Network Based on k-Means Routing -- 3.3 Coherent Robustness Training -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Evaluation Metrics -- 4.4 Baseline Methods -- 4.5 Main Results -- 4.6 Ablation Study -- 4.7 Hyperparameter Experiments -- 5 Conclusion -- References -- AVPS: Automatic Vertical Partitioning for Dynamic Workload -- 1 Introduction -- 2 AVPS Workflow -- 3 Query Encoding and Collection -- 4 Repartitioning System -- 4.1 Design of PPO Controller -- 4.2 Workload Selector -- 5 Experiment -- 5.1 Experiment Setup -- 5.2 Performance Analysis on Evaluation Model -- 5.3 Efficiency Analysis on PostgreSQL.
6 Conclusion -- References -- Multi-granularity Histories Merging Network for Temporal Knowledge Graph Reasoning -- 1 Introduction -- 2 Notations -- 3 Methodology -- 3.1 Local History Encoder -- 3.2 Attention-Based Decoder -- 3.3 Global History Gate -- 3.4 Parameter Learning -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results and Analysis -- 4.3 Ablation Study -- 4.4 Sensitivity Analysis of Global History Gate -- 4.5 Sensitivity Analysis of AttConvTransE -- 5 Conclusion -- References -- EntroMAGNN: An Entropy-Driven Metapath-Based Graph Neural Network for Maritime Emergency Event Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Graph-Based Event Prediction -- 2.2 Knowledge-Based Event Prediction -- 3 Method -- 3.1 Definition -- 3.2 Model -- 4 Experiment -- 4.1 Implementation Detail -- 4.2 Main Results -- 4.3 Ablation Study and Analysis -- 4.4 Case Study -- 5 Conclusion -- References -- Rumor Detection with News Environment Enhanced Propagation Structure -- 1 Introduction -- 2 Methodology -- 2.1 Formalization -- 2.2 Graph Construction -- 2.3 Graph Embedding -- 2.4 Classification -- 3 Experiment -- 3.1 Datasets -- 3.2 Baselines -- 3.3 Experimental Settings -- 3.4 Performance Comparison -- 3.5 Ablation Analysis -- 3.6 Case Study -- 4 Conclusion -- References -- HEAMWalk: Heterogeneous Network Embedding Based on Attribute Combined Multi-view Random Walks -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Random Walk with Attribute View -- 3.2 Selection Strategy of Structure Views Under Different Meta-Paths -- 3.3 Learning Node Embeddings by Skip-Gram -- 4 Experiment -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Node Classification -- 4.4 Node Clustering -- 4.5 Parameter Analysis -- 5 Conclusion -- References -- Spatial-Temporal Dependency Based Multivariate Time Series Anomaly Detection for Industrial Processes.
1 Introduction -- 2 Method -- 2.1 Task Formalization -- 2.2 Preliminaries -- 2.3 Framework of MTVAE-GM -- 2.4 Data Preprocessing -- 2.5 Details of MTVAE-GM -- 2.6 Joint Optimization -- 2.7 Inference -- 3 Experiments -- 3.1 Datasets and Metrics -- 3.2 Setup -- 3.3 Performance Comparison -- 3.4 Ablation Study -- 3.5 Case Study -- 4 Conclusion -- References -- A Multi-Granularity Semantic Extraction Method for Text Classification -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Overview -- 3.2 Review of BERT -- 3.3 Multi-Granularity Semantic Extraction -- 3.4 Semantic Information Fusion -- 4 Experiments and Results -- 4.1 Experimental Settings -- 4.2 Comparison with the State-of-The-Arts -- 4.3 Ablation Study -- 5 Conclusion -- References -- Modality-Guided Collaborative Filtering for Recommendation -- 1 Introduction -- 2 Methodology -- 2.1 Preliminaries -- 2.2 Overview -- 2.3 Adaptive Graph Augmentation -- 2.4 Masked Graph Autoencoder -- 2.5 Model Optimization -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Compared Baselines -- 3.3 Performance Comparison -- 3.4 Ablation Studies -- 3.5 Case Study -- 4 Conclusion -- References -- Reinforce Tokens for the Next Recommendation Generation -- 1 Introduction -- 2 Methodology -- 2.1 Preliminaries -- 2.2 Overview -- 2.3 Collaborative Signal Learning -- 2.4 Reinforced Token Generation -- 2.5 Instruction Tuning -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Compared Baselines -- 3.3 Performance Comparison -- 3.4 Ablation Studies -- 3.5 Case Study -- 4 Conclusion -- References -- Structural Optimization and Sequence Interaction Enhancement for Hyper-Relational Knowledge Graphs -- 1 Introduction -- 2 Related Work -- 2.1 Hypergraph Structural Learning -- 2.2 Hyper-Relational Knowledge Graphs Completion -- 3 Methodology -- 3.1 Model Generalization.
3.2 Importance Information Sampling for Hypergraph Structures.
Record Nr. UNINA-9910878977303321
Huang De-Shuang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part X / / edited by De-Shuang Huang, Chuanlei Zhang, Jiayang Guo
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part X / / edited by De-Shuang Huang, Chuanlei Zhang, Jiayang Guo
Autore Huang De-Shuang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (548 pages)
Disciplina 006.3
Altri autori (Persone) ZhangChuanlei
GuoJiayang
Collana Lecture Notes in Computer Science
Soggetto topico Computational intelligence
Machine learning
Computer networks
Application software
Computational Intelligence
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència computacional
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 9789819756094
981975609X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part X -- Information Security -- Eavesdropping Mobile Apps and Actions Through Wireless Traffic in the Open World -- 1 Introduction -- 2 Threat Model -- 3 System Design -- 3.1 System Overview -- 3.2 Traffic Preprocessing -- 3.3 Multi-level Feature Extraction -- 3.4 App and Action Recognition -- 4 Evaluation -- 4.1 Evaluation Methodology -- 4.2 Experimental Results -- 5 Conclusion -- References -- Improving WiFi CSI Fingerprinting with IQ Samples -- 1 Introduction -- 2 Threat Model and CSI Features -- 2.1 Threat Model -- 2.2 CSI Features -- 3 System Design -- 3.1 System Overview -- 3.2 CSI Measurement Transformation -- 3.3 Feature Extraction and Recognition -- 4 Experimental Evaluation -- 4.1 Evaluation Methodology -- 4.2 Experimental Results -- 5 Conclusions -- References -- RIHNet: A Robust Image Hiding Method for JPEG Compression -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Overview -- 3.2 Secret Image Hiding Module (SIH) -- 3.3 Classifier -- 3.4 Denoising Module -- 3.5 Loss Function -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Comparison with SOTA -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- HybridHash: An Efficient Hash Index for Encrypted Databases -- 1 Introduction -- 2 Related Work -- 3 Design of HybridHash -- 3.1 Overall Structure -- 3.2 Operations -- 4 Performance Evaluation -- 4.1 Read Performance -- 4.2 Bucket-Splitting Cost -- 4.3 Index Size -- 5 Conclusions and Future Work -- References -- Textual Backdoor Attack via Keyword Positioning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Threat Model -- 3.2 Overview -- 3.3 Calculation of the Importance Score -- 3.4 Trigger Selection -- 3.5 Generate Toxic Samples -- 3.6 Training-Time Poisoning -- 3.7 Test-Time Poisoning -- 4 Experimental Setup -- 4.1 Equipment -- 4.2 Datasets -- 4.3 Victim Models.
4.4 Baseline Methods -- 4.5 Evaluation Metrics -- 5 Experimental Results -- 5.1 Backdoor Attack Results and Discussion -- 5.2 The Impact of the Number of Operations -- 6 Conclusion -- References -- A Hybrid DCT/DST Based Embedding Framework for Video Steganography in H.265/HEVC -- 1 Introduction -- 2 Averting Intra-Distortion Drift and Spacing Coding -- 2.1 Averting Intra-Distortion Drift -- 2.2 Spacing Coding -- 3 The Architecture of the Hybrid Embedding Framework -- 3.1 Intra-Prediction Embedding and Extraction -- 3.2 Inter-Prediction Embedding and Extraction -- 4 Experimental Results -- 5 Security Analysis -- 6 Conclusion -- References -- Intelligent Computing in Computer Vision -- YOLO-FLC: Lightweight Traffic Sign Detection Algorithm -- 1 Introduction -- 2 Yolo-F -- 2.1 Improved C3 Module -- 2.2 Feature Pyramid Optimization -- 2.3 The Improvement of the Loss Function -- 2.4 Detection Scale Optimization -- 3 Model Compression -- 3.1 Pruning -- 3.2 Knowledge Distillation -- 4 Results of Experiments and Data Analysis -- 4.1 Dataset Processing -- 4.2 Evaluation Metrics -- 4.3 The Experimental Environment -- 4.4 The Experimental Results -- 5 Conclusion -- References -- Self-supervised Visual Anomaly Detection with Image Patch Generation and Comparison Networks -- 1 Introduction -- 2 Related Work -- 2.1 Unsupervised Anomaly Detection Based on Reconstruction -- 2.2 VIT-Based Network -- 2.3 Siamese Network -- 3 Method -- 3.1 VIT-Based Patch Generation Network -- 3.2 Siamese-Based Fine-Grained Comparison Network -- 3.3 Bi-directional Inference Strategy -- 4 Experiment -- 4.1 Datasets and Metrics -- 4.2 Implementation Details -- 4.3 Evaluation on MVTec AD Dataset -- 4.4 Evaluation on Our Own Dataset -- 4.5 Ablation Study -- 5 Conclusion -- References -- Spatial-Temporal Transformer Network for Continuous Action Recognition in Industrial Assembly.
1 Introduction -- 2 Related Work -- 2.1 Action Recognition for Assembly Operation -- 2.2 Human Object Interaction -- 2.3 Video Transformer -- 3 Method -- 3.1 STTN for Action Recognition -- 3.2 Operation Procedure Edition for Action Sequence Recognition -- 3.3 Continual Learning with Worker-in-the-Loop -- 4 Experiments -- 4.1 Action Recognition on Public Dataset -- 4.2 Action Recognition on Industrial Assembly Dataset -- 4.3 Promotion on Production Quality and Efficiency -- 5 Conclusion -- References -- EVF-YOLO: A Lightweight Network for License Plate Detection Under Severe Weather Conditions -- 1 Introduction -- 2 Related Work -- 3 Model Construction and Analysis -- 3.1 EMA -- 3.2 Feature Fusion V-GFPN -- 3.3 Lightweight Detection Head -- 3.4 Overall Model -- 4 Experimental Design and Result Analysis -- 4.1 Experimental Setup -- 4.2 Evaluation Metrics -- 4.3 Experimental Results -- 5 Conclusion -- References -- Quantum Robust Coding for Quantum Image Watermarking -- 1 Introduction -- 2 Proposed Method -- 2.1 Quantum Robust Coding (QRC) -- 2.2 Quantum Image Watermarking Using QRC -- 3 Experiments and Results -- 3.1 Evaluation of Watermarking with and Without QRC -- 3.2 Quantum Watermarking Evaluation by Comparison -- 4 Conclusion -- References -- Quantum-Enhanced Support Vector Machine for Large-Scale Multi-class Stellar Classification -- 1 Introduction -- 1.1 Types of Stars and Current Methods of Classification -- 2 Methodology -- 2.1 Classical Support Vector Machine -- 2.2 Quantum-Enhanced SVM with Quantum Feature Map -- 3 Feature Engineering for Stellar Classification -- 4 Results and Discussion -- 4.1 QSVM for Large Stellar Dataset with Two Classes -- 4.2 Quantum Simulator for Quantum Kernel with GPU Acceleration Using cuQuantum SDK -- 5 Conclusion -- References -- DDNet: Detection-Focused Dehazing Network -- 1 Introduction -- 2 Related Work.
2.1 Object Detection -- 2.2 Image Dehazing -- 2.3 Object Detection Under Hazy Weather -- 3 Proposed Method -- 3.1 Rep-Inception -- 3.2 Dual-Branch Fusion Network -- 3.3 Parallel Differentiable Image Processing Module -- 4 Experiments -- 4.1 Datasets -- 4.2 Comparison with Other Methods -- 4.3 Ablation Study -- 5 Conclusion -- References -- A Secure Voting Scheme Based on Quantum Walk -- 1 Introduction -- 2 Preliminary -- 2.1 One-Dimensional Quantum Walk Model on the Line -- 2.2 Teleportation Based on Quantum Walks -- 3 Security Voting Scheme -- 3.1 Quantum Voting System Model -- 3.2 Authorization of Legitimate Voters -- 3.3 Security Testing -- 3.4 Voting Scheme -- 4 Security Analysis -- 4.1 Non-reusability -- 4.2 Verifiability -- 4.3 Privacy and Security -- 4.4 Fairness -- 5 Comparison -- 6 Conclusion -- References -- PyCIM: A Python Framework for the Dynamics of Coherent Ising Machine -- 1 Introduction -- 2 The Principle of CIM -- 3 The Architecture of PyCIM -- 3.1 Existing Theoretical Models Describing CIM -- 3.2 Design of PyCIM -- 4 Experiments -- 4.1 The Evolution of DOPO State in CIM Without Coupling -- 4.2 The Process of CIM Solving MAX-CUT Problem -- 4.3 The Influence of Coupling Strength and Pump Scheduling on Solution Performance -- 4.4 The Performance of PyCIM on G-Set -- 5 Conclusion -- References -- Dense Center Point Mechanism: A Novel Approach for Multi-expert Decision Integration in Portfolio Management -- 1 Introduction -- 2 Methodology -- 2.1 Problem Definition -- 2.2 Expert Consensus Decision-Making Method -- 3 Integrate Expert Decision Process -- 3.1 Behavior and Definition of CPESM Experts -- 3.2 Portfolio Optimization of Investor -- 4 Empirical Approach -- 4.1 Experimental Setup -- 4.2 DEDIS Results Analysis -- 4.3 Portfolio Results Analysis -- 5 Conclusion -- References.
Planning for Earth Imaging Tasks via Grid Significance Mapping -- 1 Introduction -- 2 Gird Division and Mapping -- 2.1 Introducing H3 Gridding -- 2.2 Significance Mapping of Points -- 3 Task Planning Using Grid Representations -- 3.1 Grid-Based Planning Model -- 3.2 Planning Problem Solving -- 4 Experiments and Evaluation -- 4.1 Experiment Settings -- 4.2 Significance of Weight Mapping -- 4.3 Experimental Analysis of Load Balancing -- 5 Conclusion and Future Work -- References -- Virtual Reality and Human-Computer Interaction -- FusionCraft: Fusing Emotion and Identity in Cross-Modal 3D Facial Animation -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Overview -- 3.2 Preliminaries -- 3.3 Text2Avatar -- 3.4 Emotion-Identity Fusion Module -- 3.5 Avatar Generator -- 3.6 Key Points Loss -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Evaluation Methods -- 4.3 Quantitative Evaluation -- 4.4 Qualitative Evaluation -- 4.5 User Study -- 5 Limitations and Future Work -- 6 Conclusion -- References -- DWMF: A Method for Hybrid Multimodal Intent Fusion Based on Dynamic Weights -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Algorithm Description -- 3.2 Analysis of Algorithm -- 4 Experiment Steps and Results -- 4.1 Experiment Setting -- 4.2 Experiment Methods -- 4.3 Experiment Results and Analysis -- 5 Conclusion -- References -- Panoramic Video Inter Frame Prediction and Viewport Prediction Based on Background Modeling -- 1 Introduction -- 2 Related Works -- 2.1 Panoramic Video Coding -- 2.2 Viewport Prediction -- 3 Methodology -- 3.1 Background Modeling -- 3.2 Background Modeling-Based Encoding -- 3.3 Viewport Prediction -- 4 Experiments -- 4.1 Background Modeling -- 4.2 Panoramic Video Encoding -- 4.3 Viewport Prediction -- 5 Conclusion -- References.
Efficient Sensing Network and Decoupled Neural Model for Hand Pose Estimation.
Record Nr. UNINA-9910878046503321
Huang De-Shuang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part IX / / edited by De-Shuang Huang, Wei Chen, Jiayang Guo
Advanced Intelligent Computing Technology and Applications : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part IX / / edited by De-Shuang Huang, Wei Chen, Jiayang Guo
Autore Huang De-Shuang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (511 pages)
Disciplina 006.3
Altri autori (Persone) ChenWei
GuoJiayang
Collana Lecture Notes in Computer Science
Soggetto topico Computational intelligence
Machine learning
Computer networks
Application software
Computational Intelligence
Machine Learning
Computer Communication Networks
Computer and Information Systems Applications
Intel·ligència computacional
Xarxes d'ordinadors
Aprenentatge automàtic
Programari d'aplicació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 981-9756-06-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part IX -- Information Security -- Non-targeted Adversarial Attacks on Object Detection Models -- 1 Introduction -- 2 Related Work -- 2.1 Adversarial Attacks Against Classification Models -- 2.2 Adversarial Attacks Against Object Detection Models -- 2.3 Targeted Attack and Non-targeted Attack -- 3 Generate Adversarial Examples -- 3.1 Overcoming the NMS Mechanism -- 3.2 UnTargeted Adversary -- 4 Experiment -- 4.1 Experiments Setup -- 4.2 Result on Object Detection Comparison with State-Of-The-Art Methods -- 4.3 The Denseness of Proposals -- 4.4 Perceptibility -- 5 Conclusion -- References -- Block Cipher Algorithms Identification Scheme Based on KFDA -- 1 Introduction -- 2 Related Work -- 3 Block Cipher Algorithm Identification Scheme -- 3.1 Block Cipher Algorithm Identification -- 3.2 Hamming Weight Based Ciphertext Feature Extraction Method -- 3.3 Data Mapping Based on Kernel Fisher Discriminant Analysis -- 4 Experimental Preparation -- 4.1 Data Mapping Based on Kernel Fisher Discriminant Analysis -- 4.2 Graded Result Evaluation Criteria -- 5 Evaluation and Comparison of Experimental Results -- 5.1 Experimental Results of Block Cipher with Fixed Keys -- 5.2 Experimental Results of Block Cipher with Random Keys -- 6 Conclusion -- References -- Network Traffic Intrusion Detection Strategy Based on E-GraphSAGE and LSTM -- 1 Introduction -- 2 Problem Description and Methodology -- 2.1 Problem Description -- 2.2 Framework -- 2.3 Data Processing -- 2.4 Traffic Graph Construction -- 2.5 E-GraphSAGE Layer -- 2.6 LSTM Layer -- 3 Experiments and Results Analysis -- 3.1 Dataset -- 3.2 Experimental Setup -- 3.3 Experimental Metrics -- 3.4 Analysis of Results -- 3.5 Ablation Experiments -- 4 Conclusion -- References -- A State of the Art Review on Artificial Intelligence-Enabled Cyber Security in Smart Grid.
1 Introduction -- 2 Related Works -- 2.1 Security Threats -- 2.2 Artificial Intelligence and Machine Learning -- 3 Network Security in Smart Grid -- 3.1 Security Countermeasures -- 3.2 Analyzing and Comparing -- 4 AI-Based Cyber Security -- 5 Conclusion -- References -- Reversible Data Hiding Based on Octree Partitioning and Arithmetic Coding in Encrypted Three-Dimensional Mesh Models -- 1 Introduction -- 2 Proposed Method -- 2.1 Pre-processing -- 2.2 Octree-Based Spatial Subdivision and Prediction Error Detection -- 2.3 Encryption -- 2.4 Data Embedding -- 2.5 Data Extraction and Mesh Recovery -- 3 Experimental Results and Analysis -- 3.1 Embedding Capacity Analysis -- 3.2 Performance Comparison -- 3.3 Model Restoration Quality Evaluation -- 4 Conclusion -- References -- A Differential Privacy Federated Learning Scheme with Improved Noise Perturbation -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 Differential Privacy -- 3 Our Approach -- 3.1 Adjust Gradient Norm Clip Bound -- 3.2 Improved Noise Reduction -- 3.3 Privacy Cost Analysis -- 3.4 Improved Differential Privacy Federated Learning Algorithm -- 4 Experiment -- 4.1 Experiment Details -- 4.2 Private Cost -- 4.3 Accuracy -- 5 Conclusion -- References -- U-shaped Vertical Split Learning with Local Differential Privacy for Privacy Preserving -- 1 Introduction -- 2 System Design -- 2.1 Threat Model -- 2.2 System Model -- 3 Experiment -- 3.1 Experimental Settings -- 3.2 Experimental Results and Evaluation -- 4 Conclusion -- References -- An Intrusion Detection Method for Industrial Internet Fusing Multi-Scale TCN and Transformer Network -- 1 Introduction -- 2 Methodology -- 2.1 Overview of the Proposed Model -- 2.2 Improved Multi-scale Temporal Convolutional Network -- 2.3 Multiscale Patch Integrated Transformer -- 2.4 Parallel Branch Fusion -- 3 Results and Analysis.
3.1 Dataset Description -- 3.2 Evaluation Metrics -- 3.3 Implementation Details -- 3.4 Performance Comparison -- 3.5 Ablation Study -- 4 Conclusion -- References -- CSQF-BA: Efficient Container Query Technology for Cloud Security Query Framework with Bat Algorithm -- 1 Introduction -- 2 Related Work -- 2.1 Docker Applications and Docker Volume -- 2.2 Definition -- 3 Cloud Computing Security Query -- 4 Query Architecture with Docker Volume -- 5 Finding Algorithm in Volume -- 5.1 ACFA-BA, SFA-BA, and RFA-BA -- 5.2 Cloud Security Query Framework with Bat Algorithm (CSQF-BA) -- 6 Experiment -- 7 Conclusion -- References -- Full Database Reconstruction: Leakage-Abuse Attacks Based on Expected Distributions -- 1 Introduction -- 2 Model -- 2.1 Adversary Model -- 2.2 Reconstruction Attack -- 2.3 Edge Domain -- 3 Attack -- 3.1 Full Ordering Reconstruction -- 3.2 Full Database Reconstruction -- 3.3 Adaptive Attack -- 4 Experiment -- 4.1 Full Ordering Reconstruction -- 4.2 Full Database Reconstruction -- 4.3 Adaptive Attack -- 5 Conclusion and Future Work -- References -- FedURL: A BERT-based Federated Malicious URL Detection Framework -- 1 Introduction -- 2 Methodology -- 2.1 Federated Learning -- 2.2 Parameter-Efficient Fine-Tuning -- 2.3 FedURL -- 3 Experiment -- 3.1 Dataset -- 3.2 Implementation and Setup -- 3.3 Model Performance -- 3.4 Performance and Network Traffic of Federated Learning with Different Training Parts -- 3.5 Performance Comparison with Varied Client Numbers -- 3.6 Analysis of Client Number Impact on Training strategy in Federated Learning -- 3.7 Performance Evaluation using Real-world Dataset -- 4 Results and Discussion -- References -- Show Criminals' True Color: Chinese Variant Toxic Text Restoration Based on Pointer-Generator Network -- 1 Introduction -- 2 Related Work -- 2.1 Variant Toxic Text Detection and Restoration.
2.2 Pointer Mechanism -- 3 Methodology -- 3.1 Sequence-To-Sequence Model -- 3.2 Pointer-Generator Networks -- 4 Experiments Settings -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Evaluation Metric -- 5 Experiment Results and Analysis -- 5.1 Data Analysis and Variant Rules Extraction -- 5.2 Evaluation of Model Performance -- 5.3 Case Study -- 6 Conclusion -- References -- Adversarial Attacks on Network Intrusion Detection Systems Based on Federated Learning -- 1 Introduction -- 2 Adversarial Attack Scheme -- 2.1 Overview -- 2.2 Adversarial Sample Generation Method -- 2.3 Poisoning Attack Method -- 3 Experiment -- 3.1 Datasets and Evaluation Metrics -- 3.2 Experiment Results and Analysis -- 4 Conclusion -- References -- An EWMA-Based Mitigation Scheme Against Interest Flooding Attacks in Named Data Networks -- 1 Introduction -- 2 System Model -- 3 The Proposed EBMS -- 4 Performance Evaluation -- 4.1 Impacts of IFAs and bIFA on Network -- 4.2 Effectiveness of Attack Mitigation -- 5 Conclusions -- References. -- CAKGC: A Clustering Method of Cybercrime Assets Knowledge Graph Based on Feature Fusion -- 1 Introduction -- 2 Related Work -- 2.1 Detection Methods for Cybercrime Websites -- 2.2 Operation Chain of Cybercrime Underground Industry -- 2.3 Knowledge Graph Embedding -- 3 Methodology -- 3.1 Construction of Cybercrime Assets Knowledge Graph -- 3.2 Clustering of Cybercrime Assets Knowledge Graph -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Comparison Algorithms -- 4.4 Experimental Results -- 5 Conclusion -- References -- Multi-texture Fusion Attack: A Robust Adversarial Camouflage in Physical World -- 1 Introduction -- 2 Related Work -- 2.1 Physical Camouflage Attack -- 3 Method -- 3.1 The Definition of Problem -- 3.2 Framework Overview -- 3.3 Generate Adversarial Camouflage -- 3.4 Expectation Over Transformation.
3.5 Physical Transformation -- 4 Experiment -- 4.1 Experimental Setting -- 4.2 Adversarial Attack in the Digital Space -- 4.3 Adversarial Attack in the Physical Space -- 4.4 Ablation Studies -- 5 Conclusion -- References -- When Blockchain Meets Asynchronous Federated Learning -- 1 Introduction -- 2 Categorization Based on Blockchain Extensions -- 2.1 Blockchain Based on Directed Acyclic Graph -- 2.2 Traditional Blockchain -- 3 Categorization Based on Coupling Approaches -- 3.1 Fully Coupled BCFL -- 3.2 Flexibly Coupled BCFL -- 3.3 Loosely Coupled BCFL -- 4 Challenges and Future Directions -- 5 Conclusion -- References -- A High-Dimensional Data Trust Publishing Method Based on Attention Mechanism and Differential Privacy -- 1 Introduction -- 2 Preliminaries -- 2.1 Differential Privacy -- 2.2 Attention Mechanism -- 3 AMPriv Method -- 3.1 ACHD -- 3.2 NAS -- 3.3 NMEGreedybayes -- 3.4 NMENoisyConditionals -- 3.5 Sampling -- 4 Experiments -- 4.1 Experimental Environment and Setup -- 4.2 Method Performance Analysis -- 4.3 Data Availability Analysis -- 5 Conclusion -- References -- PTGroup: An Automated Penetration Testing Framework Using LLMs and Multiple Prompt Chains -- 1 Introduction -- 2 Related Work -- 2.1 Penetration Testing -- 2.2 Autonomous Agents -- 3 Methodology -- 3.1 Thought-Act-Observe Loop -- 3.2 Multi-agent Framework -- 3.3 Multiple Prompt Chains -- 4 Experiments -- 4.1 Experimental Environment -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Spammer Group Detection Approach Based on Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 2.1 Group Behavior-Based Approaches -- 2.2 Graph-Based Approaches -- 3 The Proposed Detection Method DRL-AE -- 3.1 Obtaining the Initial User Node Embeddings -- 3.2 Generating the Candidate Groups -- 3.3 Detecting Spammer Groups -- 4 Experiments -- 4.1 Experiments Datasets.
4.2 Evaluation Metrics.
Record Nr. UNINA-9910878050303321
Huang De-Shuang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
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