Artificial Neural Networks and Machine Learning – ICANN 2023

ISBN-13: 9783031441974 / Angielski / Miękka / 2023

Opis

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.  

Spis treści

2RDA: Representation and Relation Distillation with Data Augmentation.- A Document-Level Relation Extraction Framework with Dynamic Pruning.- A Global Feature Fusion Network for Lettuce Growth Trait Detection.- Adaptive Embedding and Distribution Re-Margin for Long-tail Recognition.- Adaptive Propagation Network Based on Multi-Scale Information Fusion.- An Efficient Approach for Improving the Recall of Rough Abstract Retrieval in Scientific Claim Verification.- An Explainable Feature Selection Approach for Fair Machine Learning.- Anchor link prediction based on trusted anchor re-identification.- Application of Data Encryption in Chinese Named Entity Recognition.- Attractor dynamics drive flexible timing in birdsong.- Boost Predominant Instrument Recognition Performance with MagiaSearch and MagiaClassifier.- Can Machine Learning Support Improvement in Effective Nutrition of patients in Critical Care Units?.- Cross-Domain Transformer with Adaptive Thresholding for Domain Adaptive Semantic Segmentation.- Delineation of prostate boundary from medical images via a mathematical formula-based hybrid algorithm.- Diversifying non-dissipative Reservoir Computing dynamics.- Efficient Reinforcement Learning using State-Action Uncertainty with Multiple Heads.- Exploring the role of feedback inhibition for the robustness against corruptions on event-based data.- Extracting feature space for synchronizing behavior in an interaction scene using unannotated data.- F-E Fusion:A Fast Detection Method of Moving UAV Based on Frame and Event Flow.- Few-shot Relational Triple Extraction based on Evaluation of Token-Level Semantic Similarity.- GII: a Unified Approach to Representation Learning in Open Set Recognition with Novel Category Discovery.- Glancing text and vision regularized training to enhance machine translation.- Global-Temporal Enhancement for Sign Language Recognition.- Global-to-contextual Shared Semantic Learning for Fine-grained Vision-language Alignment.- Gradient-based Learning of Finite Automata.- Hierarchical Contrastive Learning for CSI-based Fingerprint Localization.- Higher Education Programming Competencies: A Novel Dataset.- Higher Target Relevance Parallel Machine Translation with Low-Frequency Word Enhancement.- I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding.- Imbalanced Few-shot Learning based on Meta-transfer Learning.- Impact Analysis of Climate Change on Floods in an Indian Region using Machine Learning.- Improving Limited Resource Speech Recognition Performance with Latent Regression Bayesian Network.- Input Layer Binarization with Bit-Plane Encoding.- Investigation of Information Processing Mechanisms in the Human Brain during Reading Tanka Poetry.- Joint Demosaicing and Denoising with Frequency Domain Features.- Knowledge Distillation with Feature Enhancement Mask.- Label-description Enhanced Network for Few-shot Named Entity Recognition.- Landslide Surface Displacement Prediction Based on VSXC-LSTM Algorithm.- LaneMP: Robust Lane Attention Detection based on Mutual Perception of Keypoints.- LE-MVSNet: Lightweight Efficient Multi-view Stereo Network.- Lightweight Reference-Less Summary Quality Evaluation via Key Feature Extraction.- Limited Information Opponent Modeling.