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Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part I de Lazaros Iliadis

Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part I: Lecture Notes in Computer Science, cartea 14254

Editat de Lazaros Iliadis, Antonios Papaleonidas, Plamen Angelov, Chrisina Jayne
en Limba Engleză Paperback – 22 sep 2023
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.  



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Specificații

ISBN-13: 9783031442063
ISBN-10: 3031442067
Ilustrații: XXXV, 593 p. 196 illus., 172 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.87 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

A classification performance evaluation measure considering data separability.- A Cross-Modal View to Utilize Label Semantics for Enhancing Student Network in Multi-Label Classification.- A Hybrid Model Based on Samples Difficulty for Imbalanced Data Classification.- A New Dataset for Hair Follicle Recognition and Classification in Robot-Aided Hair Transplantation.- A Policy for Early Sequence Classification.- A Study of Data-driven Methods for Adaptive Forecasting of COVID-19 Cases.- An Ensemble Scheme Based on the Optimization of TOPSIS and AdaBoost for In-class Teaching Quality Evaluation.- Architecturing Binarized Neural Networks for Traffic Sign Recognition.- Boosting Few-Shot Classification with Lie Group Contrastive Learning.- Context Enhancement Methodology for action recognition in still images.- Discrete Denoising Diffusion Approach to Integer Factorization.- Distinguishing the correctness of knowledge makes knowledge transfer better.- Diversified Contrastive Learning For Few-Shot Classification.- Enhancing Cross-lingual Few-shot Named Entity Recognition by Prompt-guiding.- FAIR: A Causal Framework for Accurately Inferring Judgments Reversals.- FeatEMD: Better Patch Sampling and Distance Metric for Few-Shot Image Classification.- FFTRL: A Sparse Online Kernel Classification Algorithm for Large Scale Data.- Fusing Hand and Body Skeletons for Human Action Recognition in Assembly.- Gaze Behavior Patterns for Early Drowsiness Detection.- GH-QFL: Enhancing Industrial Defect Detection through Hard Example Mining.- HaarStyle:Revision Style Transfer Based on Multiple Resolutions.- Semi-Supervised Learning Classifier for Misinformation Related to Earthquakes Prediction on Social Media.- SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification.- Sparse Block DETR: Precise and Speedy End-to-End Detector for PCB Defect Detection.- SWP:A Sliding Window Prompt for Emotion Recognition in Conversation.- VDCNet: A Vulnerability Detection and Classification System in Cross-Project Scenarios.- CFNet: Point Cloud Upsampling via Cascaded Feedback Network.- DA-TSD: Double Attention Two-Stage 3D Object Detector from Point Clouds.- Enhanced Point Cloud Interpretation via Style Fusion and Contrastive Learning in Advanced 3D Data Analysis.- PoinLin-Net: Point Cloud Completion Network Based on Geometric Feature Extraction and Linformer Structure.- Accurate detection of spiking motifs in multi-unit raster plots.- Context-dependent computations in spiking neural networks with apical modulation.- QMTS: Fixed-point quantization for multiple-timescale spiking neural networks.- Self-Organizing Temporally Coded Representation Learning.- A System-Level Brain Model for Enactive Haptic Perception in a Humanoid Robot.- Clarifying the Half Full or Half Empty Question: Multimodal Container Classification.- CycleIK: Neuro-inspired Inverse Kinematics.- Robot at the mirror: learning to imitate via associating self-supervised models.- Approximation of Binary-Valued Functions by Networks of Finite VC Dimension.- Color-Dependent Prediction Stability of Popular CNN Image Classification Architectures.- Improving Neural Network Verification Efficiency through Perturbation Refinement.- Relative intrinsic dimensionality is intrinsic to learning.- The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning.- Componentwise Adversarial Attacks.- Decorelated Weight Initialization by Backpropagation.- Exploring individuality in human EEG using reservoir computing.- Learning efficient backprojections across cortical hierarchies in real time.- Neural self-organization for muscle-driven robots.- Novel Synthetic Data Tool for Data-Driven Cardboard Box Localization.- Reinforcement Learningwith Memory based Automatic Chunking for Complex Skill Acquisition.- Retinotopy improves the categorisation and localisation of visual objects in CNNs.- Safe Reinforcement Learning in a Simulated Robotic Arm.