Neural Information Processing -

Neural Information Processing

29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part III
Buch | Softcover
XXXVI, 722 Seiten
2023 | 1st ed. 2023
Springer International Publishing (Verlag)
978-3-031-30110-0 (ISBN)
117,69 inkl. MwSt
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.

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 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.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo XXXVI, 722 p. 248 illus., 228 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 1145 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Artificial Intelligence • Bioinformatics • Computational Intelligence • Computing Methodologies • Deep learning • Image Processing • machine learning • Neural networks • Optimization • pattern recognition • Signal Processing
ISBN-10 3-031-30110-2 / 3031301102
ISBN-13 978-3-031-30110-0 / 9783031301100
Zustand Neuware
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