
Neural Computing for Advanced Applications
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This book constitutes the refereed proceedings of the 5th International Conference on Neural Computing for Advanced Applications, NCAA 2024, held in Guilin, China, during July 5-7, 2024.
The 89 revised full papers presented in these proceedings were carefully reviewed and selected from 227 submissions. The papers are organized in the following topical sections:
Part I: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Computer vision, and their engineering applications.
Part II: Computational intelligence, nature-inspired optimizers, their engineering applications, and benchmarks.
Part III: Natural language processing, knowledge graphs, recommender systems, multimodal Deep Learning, and their applications; Fault diagnosis and forecasting, prognostic management, Time-series analysis, and cyber-physical system security.
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Content
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Natural language processing, knowledge graphs, recommender systems, multimodal Deep Learning, and their applications
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.- A Similarity Index Time-effect Collaborative Filtering Algorithm Based on Attentional Double BP Network.
.- ESert: An Enhanced Span-based Model for Measurable Quantitative Information Extraction from Medical Texts.
.- Temporal Knowledge Graph Link Prediction using Synergized Large Language Models and Temporal Knowledge Graphs.
.- A New Multi-Level Knowledge Retrieval Model for Task-Oriented Dialogue.
.- FPLGen:A Personalized Dialogue System Based on Feature Prompt Learning.
.- Ensemble learning with feature fusion for well-overflow detection.
.- CE-DSLAM:A Dynamic SLAM Framework Based on Human Contact Experience for Escort Robots.
.- EmoBART: A Multi-label Emotion Classification Method Based on Pre-Trained Label Sequence Generation Model.
.- Improving Dialogue State Tracking with Interactive Acts Attention and Attention Divergence Loss Function.
.- Psychological Consultation Dialogue Generation Based on Multi-label Classification Model and GPT.
.- DRLN: Disentangled Representation Learning Network for Multimodal Sentiment Analysis.
.- Trilinear Distillation Learning and Question Feature Capturing for Medical Visual Question Answering.
.- Multi-modal Mood Reader: Pre-trained Model Empowers Cross-Subject Emotion Recognition.
.- Rehabilitation training program recommendation system based on ALBERT-LDA model.
.- Named entity recognition of belt conveyor faults based on ALBERT-BiLSTM-SAM-CRF.
.- Explicit Facial Attribute Disentanglement for Hierarchical Relationships Detection.
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Fault diagnosis and forecasting, prognostic management, Time-series analysis, and cyber-physical system security
.
.- A Federated Learning Method for Non-Intrusive Load Monitoring Based on Fed-Prox and Bi-GRU.
.- An Interior Illuminance Prediction Model based on Differential Evolution-Gaussian Fitting.
.- Mitigating Dimensional Collapse and Model Drift in Non-IID Data of Federated Learning.
.- Wire Rope Damage Detection Method Based on Support Vector Machine Wavelet Kernel Function Algorithm.
.- Ensemble Tidal Prediction Scheme by Combining Harmonic Analysis and Meteorological Predictive Module.
.- Privacy Preserving Average Consensus via Integrable Function Based Masking.
.- Fault diagnosis of photovoltaic modules based on feature extraction.
.- A multi-scale feature adaptation ConvNeXt for cross-domain fault diagnosis.
.- Transmission Line Equipment Defect Detection Based on Improved YOLO Network.
.- A Road Defect Detection Algorithm based on Improved YOLOv8.
.- Improved road defect detection model based on RT-DETR for UAV images.
.- Blockchain-based Multi-target Distributed Passive Localization.
.- Research on Monthly Precipitation Prediction in Guangxi Based on EVO-CNN-LSTM -Attention Model.
.- Exploiting Fourier Transform for Multi-Scale Electric Load Forecasting.
.- ASTGCN for Traffic Flow Prediction Based on Weather Influence.
.- PF-BiCGAN: An Abnormal Values Replacement Approach for Port Electrical Load Forecasting.
.- Short-term load forecasting of secondary CEEMDAN-SE-Transformer BiLSTM combined with error correction.
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