Huang / Chen / Pan Advanced Intelligent Computing Technology and Applications

21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part XII
Erscheinungsjahr 2025
ISBN: 978-981-950017-8
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 553 Seiten

Reihe: Communications in Computer and Information Science

The 12-volume set CCIS 2564-2575, together with the 28-volume set LNCS/LNAI/LNBI 15842-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025.

The 523 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions.

This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".

Zielgruppe

Research

Autoren/Hrsg.

Huang, De-Shuang

Chen, Wei

Pan, Yijie

Chen, Haiming

Inhaltsverzeichnis

._Image Processing.
._Illumination-Guided Enhancement of Underexposed Fundus Images with Retinal Structural Modeling.
._DANet: Dual-stream Adaptive Interaction and Attention Fusion Network for High-Resolution Remote Sensing Cropland Change Detection.
._MLMamba: An Infrared and Visible Image Fusion Model Based on a Multi-Branch Mamba Enhanced with an Attention Mechanism.
._DualAttnADCNet: Explainable Skin Lesion Classification via Dual Attention and Dense Classifier.
._A New Target Detection Model in Complex Environments Based on Unmanned Aerial Vehicle Images.
._A Selective Fusion UNet for Coronary Artery Segmentation.
._Unpaired Artistic Portrait Drawing Generation with Asymmetric Network Knowledge Discovery and Data Mining.
._Semantic-Knowledge Infused Rule Representation Learning for Enhanced Customs Risk Rule Generation.
._Deep Knowledge Tracing Model Integrating Learning Consistency and Difficulty.
._TDSR: Temporal Dynamics Enhanced Semantic Recommendation viaCross-Domain Interactive Learning.
._Knowledge Enhanced Global Graph Contrastive Denoising for Recommendation.
._Multi-scale Fusion Recurrent Attention Framework for Time Series Forecasting.
._Denoising Multimodal Recommendation with Two-Stage Multi-View Contrastive Fusion.
._MFFKT: A Deep Knowledge Tracing Model by Fusing Multiple Learning Factors.
._Enhancing Programming Knowledge Tracing with GPT Embedding and Temporal Convolutional Network.
._VE-ResBiLSTM: A Deep Spatiotemporal Model for Field-RoadClassification with DBSCAN-Based Data Augmentation.
._Real-Time In-Class Data Mining of Moodle Click Logs for Learning Pattern Classification and Outlier Detection.
._TermRAG: Data Resource Summarization Via Term Retrieval Augmented Generation.
._AIDataSet: Knowledge Graph Construction for AI Applications.
._AFRNS: Adaptive Feature Refinement and Noise Suppression for Click-Through Rate Prediction.
._DisCoref: A Coreference Resolution Approach Based on Distence Feature for Document.
._MultiE: A Fusion of Dual-path Encoding and Multi-dimensional Adaptive Convolution for Knowledge Graph Embedding.
._Knowledge Tracking via Latent Relationship Mining and Global-Local Information Fusion.
._LE-MSF: A Chinese Medical Named Entity Recognition Method Based on Lexicon Enhancement and Multi-semantic Fusion.
._An Adaptive Masked Graph Neural Network for Graph-Based Fraud Detection.
._Leveraging Contrastive Learning to Bridge Semantic Gaps in Multimodal Recommendation.
._BOPRO: Towards new style Bayesian Optimization with Large Language Models.
._GAP: Adaptive DFS Branch-Level Parallel Subgraph Matching.
._GT-DIM: Global-Temporal Dynamic Interest Modeling for Sequential Recommendation.
._EMK-GC: An Efficient Graph Classification Solution.
._Enhanced Temporal Knowledge Graph Forecasting with Historical and Non-Historical Contrastive Learning.
._TSPN-KG: A Two-Stage Prototypical Network for Few-Shot Knowledge Graph Entity Extraction.
._Technology Opportunity Discovery with Multi-Technology Convergence Based on Knowledge-Guided Graph Representation Learning.
._XAI-Driven Academic Competence Assessment in Higher Education: A Machine Learning Framework with Dual-Explainer.
._Analogical Reasoning Enhanced Knowledge Graph Completion.
._MaTrRec: A Mamba-Transformer Framework for Robust Sequential Recommendation.
._PipeUKAN: Enhanced U-KAN with Edge Attention for Sewer Pipe Defect Segmentation.
._Robust Graph Neural Networks Against Edge Noise under Incomplete Structure Situation.
._Mobility-aware Edge Service Scheduling with Request Heterogeneity and Server Load Balancing.
._Supervised Learning.
._FECG-KD: Fisher Enhanced and Clustering Guided Knowledge Distillation for Low-bit Post-training Quantization.
._ILSPP: A Multi-Layer Security Level Phishing URL Detection Model.
._Predicting Emotions in Conversational Speech Synthesis Using Fine-Grained Historical Context.
._Code Clone-based Defect Prediction for Autonomous Driving Software.