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.
Inhaltsverzeichnis
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.
