Neural Computing for Advanced Applications
Springer Nature (Verlag)
978-981-97-7006-9 (ISBN)
The 89 revised full papers presented in these proceedings were carefully reviewed and selected from 227 submissions.
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.
.- Natural language processing, knowledge graphs, recommender systems, multimodal Deep Learning, and their applications.
.- 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.
.- 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.
| Erscheinungsdatum | 25.09.2024 |
|---|---|
| Reihe/Serie | Communications in Computer and Information Science |
| Zusatzinfo | 166 Illustrations, color; 32 Illustrations, black and white |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Informatik ► Weitere Themen ► Hardware | |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Schlagworte | Artificial Intelligence • Cloud Computing • cognitive science • computer vision • Data Mining • distributed computing methodologies • machine learning algorithms • Natural Language Processing • Neural networks |
| ISBN-10 | 981-97-7006-8 / 9819770068 |
| ISBN-13 | 978-981-97-7006-9 / 9789819770069 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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