LEADER 07804nam 22006495 450 001 9910698649403321 005 20251113184045.0 010 $a9783031301117$b(electronic bk.) 010 $z9783031301100 024 7 $a10.1007/978-3-031-30111-7 035 $a(MiAaPQ)EBC7236633 035 $a(Au-PeEL)EBL7236633 035 $a(OCoLC)1376446043 035 $a(DE-He213)978-3-031-30111-7 035 $a(PPN)26965514X 035 $a(CKB)26435306400041 035 $a(EXLCZ)9926435306400041 100 $a20230412d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e29th International Conference, ICONIP 2022, Virtual Event, November 22?26, 2022, Proceedings, Part III /$fedited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (756 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13625 311 08$aPrint version: Tanveer, Mohammad Neural Information Processing Cham : Springer International Publishing AG,c2023 9783031301100 320 $aIncludes bibliographical references and index. 327 $aApplications -- 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 SearchTasks -- 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. 330 $aThe three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22?26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13625 606 $aPattern recognition systems 606 $aData mining 606 $aMachine learning 606 $aSocial sciences$xData processing 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aComputer Application in Social and Behavioral Sciences 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aMachine learning. 615 0$aSocial sciences$xData processing. 615 14$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a006.3 702 $aTanveer$b Mohammad 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910698649403321 996 $aNeural Information Processing$92554499 997 $aUNINA