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Advanced Intelligent Computing Technology and Applications: 21st International Conference, ICIC 2025, Ningbo, China, July 2629, 2025, Proceedings, Part II [Pehme köide]

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  • Formaat: Paperback / softback, 520 pages, kõrgus x laius: 235x155 mm, 197 Illustrations, black and white; XXV, 520 p. 197 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15843
  • Ilmumisaeg: 06-Sep-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819698650
  • ISBN-13: 9789819698653
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  • Formaat: Paperback / softback, 520 pages, kõrgus x laius: 235x155 mm, 197 Illustrations, black and white; XXV, 520 p. 197 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15843
  • Ilmumisaeg: 06-Sep-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819698650
  • ISBN-13: 9789819698653
Teised raamatud teemal:

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".

.- Image Processing.
.- A Polarization-Controlled Surface Imaging Reflection Suppression Method.
.- Effective Feature Representation for Referring Video Object Segmentation.
.- An Edge Enhanced Two-Stage Network for Nuclei Segmentation.
.- Mitigating Spurious Correlations in Few-shot Classification via Bias and
Dynamic Prompt.
.- RFW-YOLO: A Multi-scale Feature Fusion Method for Infrared anti-UAV
Detection Based on WTConv.
.- Decoupled Modeling of Foreground and Background for Open-World Object
Detection.
.- TFRNet: A Text-Focused Snow Removal Network for Scene Text Recognition.
.- Revitalize Supervised Low-Light Image Enhancer: Learning Source-free Fast
Scene Adaptation.
.- DeltaDiff: Reality-Driven Diffusion with Anchor Residuals for Faithful
SR.
.- Boosting Adversarial Robustness through Structure-Guided Adversarial
Distillation.
.- DS-Net: A Local Color Complexity Prediction Network for Palette-Based
Image Recoloring.
.- SELSC: A Style Transfer Method with Style Enhancement and Localized Style
Consistency.
.- SemanticDifference: Change Detection with Multi-scale Vision-language
Representation Difference.
.- DiffEngine: Holistic Optimization of Attention and Decoder in Stable
Diffusion.
.- Hybrid Attention-Residual Networks for Hepatic and Portal Veins Semantic
Segmentation in MR Images.
.- SE-FormerSeg: Transformer Oil Leakage Detection Model based on Spatially
Enhanced Transformer Segmentation.
.- Gradient Manifold Density Fusion for 3D Object Detection.
.- TOMTrack: Multi-Object Tracking with Temporal Info, Occlusion Handling and
Object Mining.
.- GCDN: A Novel YOLOv11-Based Approach for Cotton Pest and Disease
Detection.
.- StyleCraft: High-Quality Arbitrary Style Transfer via Unified
Content-Style Fusion.
.- STINet: Spatio-Temporal Interaction Network for Remote Sensing Image
Change Detection.
.- From Ambiguity to Precision: Multimodal Chain Reasoning with Dynamic
Visual Grounding for Fine-Grained Recognition.
.- Fourier-Enhanced Swin Transformer: An Image Denoising Approach for
Intelligent Humanoid Robot Vision Systems.
.- Enhancing Remote Sensing Object Detection with LL-YOLO: Integrating
Multi-modal Data Fusion and Latent Diffusion Models.
.- Enhancing Low-Light Image Enhancement with Mamba-Integrated Dual Branch
Neural Networks.
.- An Intelligent Detection Method for Safety Equipment Non-Compliance in 
High-Altitude Power Grid Operation.
.- SGLFT-Occ: 3D Occupancy Prediction with Self-Supervised Global Local
Flatten Transformer.
.- Wavelet-Enhanced Convolution with Multiscale Aggregation Network for
Small-Target Detection in UAV Images.
.- ConvTrans-DF: A Deep Fake Detection Method Combining CNN and Transformer.
.- WW-YOLO: A Feature-Enhanced Small Object Detection Model for Drone Aerial
Image.
.- V2Tex: High-Fidelity Texture Generation for 3D Meshes from Text using
Video Diffusion Model.
.- KDA-Tuning: Knowledge-Decoupled Adapter Tuning for Vision-Language
Models.
.- HCTEdge: Optimizing Edge Detection with Augmented Local Cues and Global
Semantics.
.- A chicken counting method based on improved SORT algorithm and double
counting regions strategy.
.- Frequency-Domain Enhanced Adaptive Ensemble Adversarial Attack for
Protecting Image Privacy.
.- Annotation-free Salient Object Detection via Spatial-enhanced Contrastive
Learning and SAM.
.- A New Dual-Branch SAR Image Interference Suppression Method.
.- QuerySS3D: Boosting Semi-Supervised 3D Object Detection via Image Query.
.- Oracle Bone Inscriptions Recognition Based on Spatial Transformer Network
and Few-shot Learning.
.- Refine Outline First: Mask-Based Point-Image Model for Efficient Point
Cloud Completion.
.- AFEI-Net: A Infrared Ship Detection Network Based on Adaptive Feature
Selection and Edge Information Enhancement.
.- EGAP-YOLO: An Efficient Crack Detection Model Based on YOLO Architecture.
.- Robust Non-Rigid Point Set Registration with Adaptive Rigidity and Global
Normal Consistency.