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Advanced Intelligent Computing Technology and Applications: Lecture Notes in Computer Science, cartea 15848

Editat de De-Shuang Huang, Yijie Pan, Wei Chen, Bo Li
en Limba Engleză Paperback – 22 iul 2025
.- 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.
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Specificații

ISBN-13: 9789819698745
ISBN-10: 981969874X
Pagini: 548
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.82 kg
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science