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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 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial neural networks and machine learning - ICANN 2023/ edited by Lazaros Iliadis ... [et al.].
Reminder of title:	32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26-29, 2023 : proceedings.
remainder title:	ICANN 2023
other author:	Iliadis, Lazaros S.
corporate name:	International Conference on Artificial Neural Networks (European Neural Network Society)
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	xxxv, 593 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	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 Learning with 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.
Contained By:	Springer Nature eBook
Subject:	Neural networks (Computer science) - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-44207-0
ISBN:	9783031442070

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 /
Artificial neural networks and machine learning - ICANN 202332nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26-29, 2023 : proceedings.Part I /[electronic resource] :ICANN 2023edited by Lazaros Iliadis ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xxxv, 593 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,142540302-9743 ;. - Lecture notes in computer science ;14254..

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 Learning with 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.

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.

ISBN: 9783031442070

Standard No.: 10.1007/978-3-031-44207-0doiSubjects--Topical Terms:

582186
Neural networks (Computer science)
--Congresses.

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

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 /
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