Artificial Neural Networks and Machine Learning ¿ ICANN 2023
32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26¿29, 2023, Proceedings, Part VII Herausgegeben:Iliadis, Lazaros; Papaleonidas, Antonios; Angelov, Plamen; Jayne, Chrisina
Artificial Neural Networks and Machine Learning ¿ ICANN 2023
32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26¿29, 2023, Proceedings, Part VII Herausgegeben:Iliadis, Lazaros; Papaleonidas, Antonios; Angelov, Plamen; Jayne, Chrisina
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.
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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Inhaltsangabe
A Shallow Information Enhanced Efficient Small Object Detector based on YOLOv5.- Adaptive Dehazing YOLO for Object Detection.- Adaptive Training Strategies for Small Object Detection using Anchor-based Detectors.- Automatic Driving Scenarios: A Cross-Domain Approach for Object Detection.- Dual Attention Feature Fusion for Visible-Infrared Object Detection.- Feature Sniffer: A Stealthy Inference Attacks Framework on Split Learning.- Few-Shot Object Detection via Transfer Learning and Contrastive Reweighting.- GaitFusion: Exploring the fusion of silhouettes and optical flow for gait recognition.- Gradient Adjusted and Weight Rectified Mean Teacher for Source-free Object Detection.- IMAM: Incorporating multiple attention mechanisms for 3D Object Detection from Point Cloud.- LGF2: Local and Global Feature Fusion for Text-guided Object Detection.- MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection.- Object Detection inFoggy Images with Transmission Map Guidance.- PE-YOLO: Pyramid Enhancement Network for Dark Object Detection.- Region Feature Disentanglement for Domain Adaptive Object Detection.- ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion.- SDGC-YOLOv5: A more accurate model for small object detection.- The Statistical Characteristics of P3a and P3b Subcomponents in Electroencephalography Signals.- Transforming Limitations into Advantages: Improving Small Object Detection Accuracy with SC-AttentionIoU Loss Function.- Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer.- X-shape Feature Expansion Network for Salient Object Detection in Optical Remote Sensing Images.- Aggregate Distillation For Top-K Recommender System.- Candidate-Aware Dynamic Representation for News Recommendation.- Category Enhanced Dual View Contrastive Learning for Session-based Recommendation.- Electronic Medical Record Recommendation System Based on Deep Embedding Learning with Named Entity Recognition.- Incremental Recommendation Algorithm based on the Influence Propagation Model.- Scenic Spot Recommendation Method Integrating Knowledge Graph And Distance Cost.- A Unified Video Semantics Extraction and Noise Object Suppression Network for Video Saliency Detection.- Adaptive Token Excitation With Negative Selection For Video-Text Retrieval.- Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization.- Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition.- Correction while Recognition: Combining Pretrained Language Model for Taiwan-accented Speech Recognition.- Cross-Camera Prototype Learning for Intra-Camera Supervised Person Re-Identification.- ECDet: A Real-time Vehicle Detection Network for CPU-only Devices.- Gated Multi-Modal Fusion with Cross-Modal Contrastive Learning for VideoQuestion Answering.- Learning Video Localization on Segment-Level Video Copy Detection with Transformer.- Linear Transformer-GAN: A Novel Architecture to Symbolic Music Generation.- MBMS-GAN: Multi-Band Multi-Scale Adversarial Learning for Enhancement of Coded Speech at Very Low Rate.- OWS-Seg: online weakly supervised video instance segmentation via contrastive learning.- Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition.- Self-Supervised Video Object Segmentation Using Motion Feature Compensation.- Space-Time Video Super-Resolution Based on Long-Term Time Dependence.
A Shallow Information Enhanced Efficient Small Object Detector based on YOLOv5.- Adaptive Dehazing YOLO for Object Detection.- Adaptive Training Strategies for Small Object Detection using Anchor-based Detectors.- Automatic Driving Scenarios: A Cross-Domain Approach for Object Detection.- Dual Attention Feature Fusion for Visible-Infrared Object Detection.- Feature Sniffer: A Stealthy Inference Attacks Framework on Split Learning.- Few-Shot Object Detection via Transfer Learning and Contrastive Reweighting.- GaitFusion: Exploring the fusion of silhouettes and optical flow for gait recognition.- Gradient Adjusted and Weight Rectified Mean Teacher for Source-free Object Detection.- IMAM: Incorporating multiple attention mechanisms for 3D Object Detection from Point Cloud.- LGF2: Local and Global Feature Fusion for Text-guided Object Detection.- MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection.- Object Detection inFoggy Images with Transmission Map Guidance.- PE-YOLO: Pyramid Enhancement Network for Dark Object Detection.- Region Feature Disentanglement for Domain Adaptive Object Detection.- ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion.- SDGC-YOLOv5: A more accurate model for small object detection.- The Statistical Characteristics of P3a and P3b Subcomponents in Electroencephalography Signals.- Transforming Limitations into Advantages: Improving Small Object Detection Accuracy with SC-AttentionIoU Loss Function.- Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer.- X-shape Feature Expansion Network for Salient Object Detection in Optical Remote Sensing Images.- Aggregate Distillation For Top-K Recommender System.- Candidate-Aware Dynamic Representation for News Recommendation.- Category Enhanced Dual View Contrastive Learning for Session-based Recommendation.- Electronic Medical Record Recommendation System Based on Deep Embedding Learning with Named Entity Recognition.- Incremental Recommendation Algorithm based on the Influence Propagation Model.- Scenic Spot Recommendation Method Integrating Knowledge Graph And Distance Cost.- A Unified Video Semantics Extraction and Noise Object Suppression Network for Video Saliency Detection.- Adaptive Token Excitation With Negative Selection For Video-Text Retrieval.- Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization.- Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition.- Correction while Recognition: Combining Pretrained Language Model for Taiwan-accented Speech Recognition.- Cross-Camera Prototype Learning for Intra-Camera Supervised Person Re-Identification.- ECDet: A Real-time Vehicle Detection Network for CPU-only Devices.- Gated Multi-Modal Fusion with Cross-Modal Contrastive Learning for VideoQuestion Answering.- Learning Video Localization on Segment-Level Video Copy Detection with Transformer.- Linear Transformer-GAN: A Novel Architecture to Symbolic Music Generation.- MBMS-GAN: Multi-Band Multi-Scale Adversarial Learning for Enhancement of Coded Speech at Very Low Rate.- OWS-Seg: online weakly supervised video instance segmentation via contrastive learning.- Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition.- Self-Supervised Video Object Segmentation Using Motion Feature Compensation.- Space-Time Video Super-Resolution Based on Long-Term Time Dependence.
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