{"product_id":"image-and-graphics-9789819533978","title":"Image and Graphics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003c!--StartFragment --\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003ePart\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e1 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eArtificial Intelligence:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- SRG-Net: Semantic Relation-Guided Network for Commonsense Video Captioning.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- EAANet: Edge-Aware Attention Network for Real-Time Road Scene Understanding.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Learning A Decomposition-Driven Two Stages Unfolding Artifact Removal Network for Compressed Images.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Martingale-Based Skin Lesion Segmentation from Dermoscopic Images.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Research on Adaptive Multi-layer Multi-pass Welding Technology for Medium-Thick Plates.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- M³E: Mixture of Multi-scale Multi-modal Experts for Time Series Forecasting.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- PoseCLR Bridging 2D and 3D Pose Representations via Contrastive Learning for Action Recognition.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Art3D-Fusion: A Hybrid Framework for Visual Synthesis with Artistic Control.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Lesion Localization Prior-Driven Few-Shot Learning for Branch Atheromatous Disease Diagnosis.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Deep Multi-Sentence Aligned Cross-Modal Retrieval.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Single-Layer Denoising Taylorformer for UAV Nighttime Tracking.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Position-Aware Text-to-Image Generation with Efficient Controllability.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Introducing DINOv2 for Medical Image Boundary Tracking.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Adaptive Pruning and Cross-Domain Feature Fusion for Robust Object Tracking.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Data Leakage Detection in Large Vision-Language Models via Multimodal Perturbation.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- A Novel Dual-Branch Cross-Attention Transformer Network for Low-Dose CT Denoising.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- TCGFNet: Multi-Scale Transformer-Convolution with Geometry-Guided Feedback for Robust Point Cloud Denoising.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Adversarial Iterative Pre-Enactment Framework for Air Combat Based on Mental Simulation Theory.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- SA-Pillar: Structure-Aware Feature Learning for Real-Time 3D Object Detection.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Knowledge-aware Intent Subgraph Learning for Recommendation.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- PF-DETR:Enhanced DETR with Pre-Encoded Feature Fusion for Small and Multi-Scale Object Detection in UAV Imagery.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Selective Labeling for 3D Shape Label Transfer based on Local-Global Features.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e.- Part\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e2 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eBiological and Medical Image Processing:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- MAA-Net: A Multi-Attention Aggregation Network for Segmentation of Key Structures in Microvascular Decompression.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Contrastive Hierarchical Graph based Multiple Instance Learning for Fundus Screening\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Polyp Segmentation based on Edge Guidance.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- A Deep Unfolding based on U-Net Graph-Guided Hybrid Regularization  method for Bioluminescence Tomography.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- CMambaR: Cardiac Phase Embedded Vision  Mamba for Accelerating Cardiac MRI  Reconstruction.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- SC-DSE-nnUNet: An Efficient Hippocampus MRI Segmentation Method.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Spatiotemporal Feature Fusion for Glioblastoma Recurrence Prediction Using Mamba-Based Dual-Stream Framework.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Automatic and Fast Segmentation of Cochlear Implant-Induced Artifacts in MR Images Using Deep Learning.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e.- Part\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e3 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eColor and Multispectral Processing:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- End-to-End Diffusion Models with Physics Priors for Enhanced Spectral Super-Resolution.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Asymmetric Dual-Teacher Guided Knowledge Distillation for HSI-SR with Reconstructed Features.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Gradient-based multi-focus image fusion with  focus-aware saliency enhancement.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- OME-Net: Optimization-inspired Multi-domain Enhanced Network for Image Compressed Sensing Reconstruction.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e.- Part\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e4 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eCompression, Transmission, Retrieval:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- MARSNet: Scalable Deep Coding of LiDAR Point Clouds via Multimodal and Residual Learning.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Accelerating Learned Video Compression via Low-Resolution Representation Learning.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Optical Flow-driven Fast CU Partition for Inter Prediction in Versatile Video Coding.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Semantic Maintained Video Compression by Background Blurring in Surveillance Scenarios.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Learning Based Fast Coding Unit Decision for Video-based Point Cloud Compression.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e.- Part\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e5 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eComputational Imaging:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Leveraging a Dual-Learning Methodology Based on Degradation Modeling and Fractional Fourier Image Transformer for Light Field Image Super-Resolution.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Video Stabilization Based on MeshFlow Motion Model in Dynamic and Complex Scenes.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003eDual-Edge Consistency Constrained Unfolding Network for Depth Map Super-Resolution.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e.- Part\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e6 \u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"ZH-CN\" style=\"font-family: DengXian; mso-ascii-font-family: Aptos; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-font-family: Aptos; mso-hansi-theme-font: minor-latin;\"\u003e:\u003c\/span\u003eComputer Graphics and Visualization:\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Isotropic Remeshing with Inter-Angle Optimization.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- AlignMR: Design of a Home Yoga Self Learning System Based on MR Technology.\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e.- Bi-IRNet: A Transformer-based Binaural Impulse Response Generation Guidance Model.\u003c\/p\u003e\u003cp\u003e\u003c!--EndFragment --\u003e\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53212856451415,"sku":"9789819533978","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/image-and-graphics-9789819533978","provider":"Book Curl","version":"1.0","type":"link"}