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| Titolo: |
Neural information processing : 29th international conference, ICONIP 2022, virtual event, November 22-26, 2022, proceedings, Part III / / Mohammad Tanveer [and four others], editors
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| Pubblicazione: | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] |
| ©2023 | |
| Edizione: | 1st ed. 2023. |
| Descrizione fisica: | 1 online resource (756 pages) |
| Disciplina: | 006.3 |
| Soggetto topico: | Neural computers |
| Neural networks (Computer science) | |
| Persona (resp. second.): | TanveerMohammad |
| Nota di bibliografia: | Includes bibliographical references and index. |
| Nota di contenuto: | Applications -- A Comparative Analysis of Loss Functions for Handling Foreground-Background Imbalance in Image Segmentation -- Electron Microscopy Image Registration with Transformers -- Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network -- A Measurement-Based Quantum-Like Language Model for Text Matching -- Virtual Try-On via Matching Relation with Landmark -- WINMLP:Quantum&Involution Inspire False Positive Reduction In Lung Nodule Detection -- Incorporating Generation Method and Discourse Structure to Event Coreference Resolution -- CCN: Pavement Crack Detection With Context Contrasted Net -- Spatial and Temporal Guidance for Semi-supervised Video Object Segmentation -- A Hybrid Framework based on Classifier Calibration for Imbalanced Aerial Scene Recognition -- Enhancing BERT for Short Text Classification with Latent Information -- Unsupervised Anomaly Segmentation for Brain Lesions using Dual Semantic-Manifold Reconstruction -- Transformer Based High-frequency Predictive Model for Visual-haptic Feedback of Virtual Surgery Navigation -- Hierarchical Multimodal Attention Network Based on Semantically Textual Guidance for Video Captioning -- Autism Spectrum Disorder Classification of Facial Images using Xception Model and Transfer Learning with Image Augmentation -- A Comprehensive Vision-based Model for Commercial Truck Driver Fatigue Detection -- Automatic Identification of Class Level Refactoring using Abstract Syntax Tree and Embedding Technique -- Universal Distributional Decision-based Black-box Adversarial Attack with Reinforcement Learning -- Detecting and Mitigating Backdoor Attacks with Dynamic and Invisible Triggers -- NAS-StegNet: Lightweight Image Steganography Networks via Neural Architecture Search -- FIT: Frequency-based Image Translation for Domain Adaptive Object Detection -- Single Image Dehazing Using Frequency Attention -- A Recurrent Point Clouds Selection Method for 3D Dense Captioning -- Multi-domain Feature Fusion Neural Network for Electrocardiogram Classification -- Graph-based Contextual Attention Network for Single Image Deraining -- ADTR: Anomaly Detection Transformer with Feature Reconstruction -- SCIEnt: A Semantic-feature-based Framework for Core Information Extraction from Web Pages -- Hierarchical down-sampling based ultra high-resolution image inpainting -- Vision Transformer With Depth Auxiliary Information For Face Anti-spoofing -- Dynamically Connected Graph Representation For Object Detection -- Multi-Class Anomaly Detection -- Understanding Graph and Understanding Map and their Potential Applications -- BBSN: Bilateral-Branch Siamese Network for Imbalanced Multi-label Text Classification -- Deep Hierarchical Semantic Model for Text Matching -- Multimodal Neural Network For Demand Forecasting -- Image Super-Resolution Based on Adaptive Feature Fusion Channel Attention -- SGFuion:Camera-LiDAR Semantic and Geometric Fusion for 3D Object Detection -- SATNet: Captioning with Semantic Alignment and Feature Enhancement -- Halyomorpha Halys Detection Using Efficient Neural Networks -- HPointLoc: Point-based Indoor Place Recognition using Synthetic RGB-D Images -- In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers -- Relation-guided Dual Hash Network for Unsupervised Cross-Modal Retrieval -- Prompt-Based Learning for Aspect-Level Sentiment Classification -- Multi-Knowledge Embeddings Enhanced Topic Modeling for Short Texts -- Adaptive early classification of time series using deep learning -- Introducing Multi-modality in Persuasive Task Oriented Virtual Sales Agent -- Low Dose CT Image Denoising Using Efficient Transformer With SimpleGate Mechanism -- iResSENet: An Accurate Convolutional Neural Network for Retinal Blood Vessel Segmentation -- Evolutionary Action Selection for Gradient-based Policy Learning -- Building Conversational Diagnosis Systems for Fine-grained Diseases using Few Annotated Data -- Towards Improving EEG-based Intent Recognition in Visual Search Tasks -- RVFL Classifier based Ensemble Deep Learning for Early Diagnosis of Alzheimer’s Disease -- Anatomical Landmarks Localization for 3D Foot Point Clouds -- Impact of the composition of feature extraction and class sampling in medicare fraud detection -- A Hybrid Feature Selection Approach for Data Clustering Based on Ant Colony Optimization -- FaceMix: Transferring local regions for data augmentation in face recognition -- Permissioned Blockchain-based XGBoost for Multi Banks Fraud Detection -- Rethinking Image Inpainting with Attention Feature Fusion -- Towards Accurate Alignment and Sufficient Context in Scene Text Recognition. |
| Sommario/riassunto: | The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. |
| Titolo autorizzato: | Neural Information Processing ![]() |
| ISBN: | 9783031301117 |
| 9783031301100 | |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 996525671703316 |
| Lo trovi qui: | Univ. di Salerno |
| Opac: | Controlla la disponibilità qui |