Hosszú leírás:

The two-volume set LNAI 15497 and LNAI 15498 constitutes the refereed proceedings of the 14th International Conference on Brain Inspired Cognitive Systems, BICS 2024, held in Hefei, China, during December 6?8, 2024. 

The 56 full papers presented in these two volumes were carefully reviewed and selected from 124 submissions.

These papers deal with various aspects of brain inspired cognitive systems, focusing on latest advancements in brain-inspired computing; artificial intelligence; and cognitive systems.

Tartalomjegyzék:

.- Multi-Modal Dynamic Information Selection Pyramid Network for Alzheimer?s Disease Classification.

.- Text-Guided Vision Mamba for Alzheimer?s Disease Prediction using 18F-FDG PET.

.- EEG-based Recognition of Knowledge Acquisition States in Second Language Learning.

.- A study on the neural mechanism of the spatial position of speech in different masking types affecting auditory attention processing.

.- DSCF-DE: A Query-based Object Detection Model via Dynamic Sampling and Cascade Fusion.

.- MDFNet: Multi-Dimensional Fusion Attention for Enhanced Image Captioning.

.- Dynamic Points Location of Professional Model Pose Based on Improved Network Stacking Model.

.- A Redundancy Free Facial Acne Detection Framework Based on Multi-view Dermoscopy Images Stitching.

.- A New Device Placement Approach with Dual Graph Mamba Networks and Proximal Policy Optimization.

.- Cross-Generational Contrastive Continual Learning for 3D point cloud semantic segmentation.

.- TGAM-SR: A Sequential Recommendation Model for Long And Short-Term Interests Based on TCN-GRU And Atten-tion Mechanism.

.- Investigating ChatGPT?s Translation Hallucination from an Embodied-Cognitive Translatology Perspective.

.- A Study on Chinese Acronym Prediction Based on Contextual Thematic Consistency.

.- Learning Supportive Two-Stream Network for Audio-Visual Segmentation.

.- Multi-exposure Driven Stable Diffusion for Shadow Removal.

.- Human disease prediction based on symptoms using novel machine learning.

.- CAT-LCAN: A Multimodal Physiological Signal Fusion Framework for Emotion Recognition.

.- A novel thermal imaging and machine learning based privacy preserving framework for efficient space allocation, utilisation and management.

.- Training Feature-Awared GPU-Memory Allocation and Management for Deep Neural Networks.

.- TR-LDA: An Improved Potential Topic Recognition Model.

.- Brain-inspired object domain adaptive segmentation.

.- Task adaptive feature distribution based network for few-shot fine-grained target classification.

.- ST TransNeXt: A Novel Pig Behavior Recognition Model.

.- A Method for Predicting The RUL of HDDs Based on Bidirectional LSTM and Transformer.

.- Spatio-temporal Graph Learning on Adaptive Mined Key Frames for High-performance Multi-Object Tracking.

.- From image to the ground: Recover the ground location of vehicles from traffic cameras using neural networks.

.- In-depth Evaluation and Analysis of Hyperspectral Unmixing Algorithms with Cognitive Models.

.- Effective Gas Classification using Singular Spectrum Analysis and Random Forest in Electronic Nose Applications.