Advanced Intelligent Computing Technology and Applications : 21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part I / edited by De-Shuang Huang, Yijie Pan, Wei Chen, Bo Li.

Format:

• Book

Author/Creator:

• Huang, De-Shuang.

Contributor:

• Pan, Yijie.
• Chen, Wei.
• Li, Bo.

Series:

• Lecture Notes in Computer Science, 1611-3349 ; 15842

Language:

English

Subjects (All):

• Computational intelligence.
• Computer networks.
• Machine learning.
• Application software.
• Computational Intelligence.
• Computer Communication Networks.
• Machine Learning.
• Computer and Information Systems Applications.

Local Subjects:

• Computational Intelligence.
• Computer Communication Networks.
• Machine Learning.
• Computer and Information Systems Applications.

Physical Description:

1 online resource (888 pages)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total of 1206 regular papers 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".

Contents:

• Image Processing .
• Graph Sampling Transformer for HSI Classification.
• Selective Targeting for Enhanced Salient Object Detection.
• ALD-Net: Adaptive Local Diffusion Network for Ethnic Pattern Synthesis.
• ISTD-YOLO: A Multi-Scale Lightweight High-Performance Infrared Small Target Detection Algorithm.
• DBTNet: Dual-Stream Background-Target Decoupling Network for Infrared Small Target Detection.
• STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking.
• Semantic-Guided Multi-Attention Model for Infrared and Visible Image Fusion: A Deep Learning Approach.
• Feature-guided Prototype-enhanced Few-shot Semantic Segmentation Model.
• Image Aesthetic Quality Assessment Method Based on Multi-Scale Fusion Spiking Neural Network Vision Transformer.
• Feature-Augmented Segment Anything Model for Salient Object Detection in Optical Remote Sensing Images.
• DDECNet: Dual-Branch Difference Enhanced Network with Novel Efficient Cross-Attention for Remote Sensing Change Detection.
• Remote Sensing Image Change Detection Based on Wavelet Feature Interaction and Multi-Scale Feature Aggregation.
• Depixelation and Enhancement Algorithm of Fiber Bundle Images Based on Diffusion Model.
• MambaSTR: Scene Text Recognition with Masked State Space Model.
• MambaFER: A Mamba-Based Dual-Perception Network for Facial Expression Recognition in the Wild.
• A Steel Surface Defect Detection Method Based on a Lightweight Semantic Segmentation Model.
• YOLO-CBD: A Classroom Behavior Detection Method.
• Optimizing Small Object Detection in Drone Imagery: A Lightweight Weighted Multi-Branch Supportive Fusion.
• Test-Time Adaptation via Distribution-Aware Guidance for Vision-Language Models.
• GDAFormer: Transformer-Driven Fundus Image Enhancement with Gated Dual-Attention.
• Change Detection for Wide-Field Video Images in Foggy Weather Based on Enhanced K-Means Clustering.
• PML-SLAM: Optimizing and Enhancing Visual SLAM with Point-to-Line Matching.
• RGPest-YOLO: A YOLOv8 Pest Detection Method Based on Image Preprocessing.
• IRAWildNet: A Multi-Species Infrared Wildlife Target Detection Method from the UAV Perspective.
• FTDB-Net: A Fourier Transform-Based Dual-Branch Low-Light Image Enhancement Network.
• Curriculum-Learned Masked Pretraining Models for Remote Sensing Building Detection.
• End-to-End Landmark Guided Head Pose Estimation.
• JPEG Image Encryption with Cross-Channel Permutation and Tunable Range Substitution.
• ERUAVNet: An Efficient Reparameterized Network for Unmanned Aerial Vehicle Detection.
• Modality Perception Network for Multi-Modal Rumor Detection.
• Dual-Branch Diffusion Model for JPEG Artifact Correction.
• Enhancing H&E-to-IHC Virtual Staining via Multi-Channel Correlation Learning.
• HASNet: A Hybrid CNN-Transformer Network with Adaptive Sparse Cross Attention for Low-Light Image Enhancement.
• Multi-View 3D Object Detection by Using a Preluded 2D Detector.
• A L0 Framework with Anisotropic Sparsity and Fairness for 3D Denoising.
• Real-Time Semantic Segmentation for UAV Perspectives on Embedded Platforms.
• FDRFCD: Feature Disentangling Representation and Fusion Deep Network for Remote Sensing Image Change Detection.
• WSFFormer: LightWeight Wavelet Spatial-Frequency Vision Transformer for Visual Representation Learning.
• Pose-Enhanced 3D Rotary Embedding for Multi-View 3D Object Detection.
• Exploratory Study on Enhancing Generalization Performance of Transformer Architectures in MedicalImage Segmentation: A Survey.
• Planar KNN for Multi-Camera Interference Mitigation of Point Cloud.
• Frequency-Enhanced Part Feature Mining and Cross-Modality Alignment for Visible-Infrared Person Re-Identification.
• SRL-UNet: An Improved Residual U-Net with 2D-Selective-Scan for Nuclear Segmentation.

ISBN:

981-9698-63-4