Neural Information Processing
Springer International Publishing (Verlag)
978-3-030-92184-2 (ISBN)
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic.
The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows:
Part I: Theory and algorithms;
Part II: Theory and algorithms; human centred computing; AI and cybersecurity;
Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications;
Part IV: Applications.
Theory and Algorithms.- Metric Learning Based Vision Transformer for Product Matching.- Stochastic Recurrent Neural Network for Multistep Time Series Forecasting.- Speaker Verification with Disentangled Self-Attention.- Multi Modal Normalization.- A Focally Discriminative Loss for Unsupervised Domain Adaptation.- Automatic Drum Transcription with Label Augmentation using Convolutional Neural Networks.- Adaptive Curriculum Learning for Semi-Supervised Segmentation of 3D CT-Scans.- Genetic Algorithm and Distinctiveness Pruning in the Shallow Networks for VehicleX.- Stack Multiple Shallow Autoencoders into A Strong One: A New Reconstruction-based Method to Detect Anomaly.- Learning Discriminative Representation with Attention and Diversity for Large-scale Face Recognition.- Multi-task Perceptual Occlusion Face Detection with Semantic Attention Network.- RAIDU-Net: Image Inpainting via Residual Attention Fusion and Gated Information Distillation.- Sentence Rewriting with Few-Shot Learningfor Document-Level Event Coreference Resolution.- A Novel Metric Learning Framework for Semi-supervised Domain Adaptation.- Generating Adversarial Examples by Distributed Upsampling.- CPSAM: Channel and Position Squeeze Attention Module.- A Multi-Channel Graph Attention Network for Chinese NER.- GSNESR: A Global Social Network Embedding Approach for Social Recommendation.- Classification Models for Medical Data with Interpretative Rules.- Contrastive Goal Grouping for Policy Generalization in Goal-Conditioned Reinforcement Learning.- Global Fusion Capsule Network with Pairwise-Relation Attention Graph Routing.- MA-GAN: A Method Based on Generative Adversarial Network for Calligraphy Morphing.- One-Stage Open Set Object Detection with Prototype Learning.- Aesthetic-aware Recommender System for Online Fashion Products.- DAFD: Domain Adaptation Framework for Fake News Detection.- Document Image Classification Method based on Graph Convolutional Network.- Continual Learning of 3D Point Cloud Generators.- Attention-Based 3D ResNet for Detection of Alzheimer's Disease Process.- Generation of a Large-Scale Line Image Dataset with Ground Truth Texts from Page-Level Autograph Documents.- DAP-BERT: Differentiable Architecture Pruning of BERT.- Trash Detection On Water Channels.- Tri-Transformer Hawkes Process: Three Heads are better than one.- PhenoDeep: A deep Learning-based approach for detecting reproductive organs from digitized herbarium specimen images.- Document-level Event Factuality Identification using Negation and Speculation Scope.- Dynamic Network Embedding by Time-Relaxed Temporal Random Walk.- Dual-band Maritime Ship Classification based on Multi-layer Convolutional Features and Bayesian Decision.- Context-Based Anomaly Detection via Spatial Attributed Graphs in Human Monitoring.- Domain-Adaptation Person Re-Identification via Style Translation and Clustering.- Multimodal Named Entity Recognition Via Co-attention-based Method with Dynamic Visual Concept Expansion.- Ego Networks.- Cross-modal based Person Re-Identification via Channel Exchange and adversarial Learning.- SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs.- Deep Neuroevolution: Training Neural Networks using a Matrix-free Evolution Strategy.- Weighted P-Rank: A Weighted Article Ranking Algorithm Based on a Heterogeneous Scholarly Network.- Clustering Friendly Dictionary Learning.- Understanding Test-Time Augmentation.- SphereCF: Sphere Embedding for Collaborative Filtering.- Concordant Contrastive Learning for Semi-supervised Node Classification on Graph.- Improving Shallow Neural Networks via Local and Global Normalization.- Underwater Acoustic Target Recognition with Fusion Feature.- Evaluating Data Characterization Measures for Clustering Problems in Meta-learning.- ShallowNet: An Efficient Lightweight Text Detection Network Based on Instance Count-aware Supervision Information.- Image Periodization for Convolutional NeuralNe
| Erscheinungsdatum | 07.12.2021 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
| Zusatzinfo | XXV, 695 p. 28 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1092 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Applications • Artificial Intelligence • Computer Science • computer vision • conference proceedings • Databases • Data Mining • Deep learning • Image Processing • image reconstruction • Image Segmentation • Imaging Systems • Informatics • Information Retrieval • learning • machine learning • Network Protocols • Neural networks • pattern recognition • Research • Signal Processing |
| ISBN-10 | 3-030-92184-0 / 3030921840 |
| ISBN-13 | 978-3-030-92184-2 / 9783030921842 |
| Zustand | Neuware |
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