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Digital Multimedia Communications: 21st International Forum on Digital TV and Wireless Multimedia Communications, IFTC 2024, Hainan, China, November 2829, 2024, Revised Selected Papers, Part I [Pehme köide]

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  • Formaat: Paperback / softback, 435 pages, kõrgus x laius: 235x155 mm, 161 Illustrations, color; 5 Illustrations, black and white; XIX, 435 p. 166 illus., 161 illus. in color., 1 Paperback / softback
  • Sari: Communications in Computer and Information Science 2441
  • Ilmumisaeg: 09-Apr-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819642752
  • ISBN-13: 9789819642755
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Digital Multimedia Communications: 21st International Forum on Digital TV and Wireless Multimedia Communications, IFTC 2024, Hainan, China, November 2829, 2024, Revised Selected Papers, Part ISuurem pilt
  • Formaat: Paperback / softback, 435 pages, kõrgus x laius: 235x155 mm, 161 Illustrations, color; 5 Illustrations, black and white; XIX, 435 p. 166 illus., 161 illus. in color., 1 Paperback / softback
  • Sari: Communications in Computer and Information Science 2441
  • Ilmumisaeg: 09-Apr-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819642752
  • ISBN-13: 9789819642755
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789819642755.html
Märksõnad:
This volume contains 28 selected papers presented at IFTC 2024: 21st International Forum of Digital Multimedia Communication, held in Lingshui, Hainan, China, on November 28-29, 2024.



The 55 full papers included in this 2-volume set were carefully reviewed and selected from 146 submissions. They were organized in topical sections as follows:



CCIS 2441: Affective Computing, Graphics & Image Processing for Virtual Reality, Large Language Models, Multimedia Communication, Application of Deep Learning and Video Analysis.



CCIS 2442: Human and Interactive Media, Image Processing, Quality Assessment and Source Coding.
Spatio-Temporal Scene Graph Reasoning Networks for Emotion Recognition
in User-Generated Videos.- Unsupervised 3D Face Reconstruction Method Based
on ITV-Net.- Attention-Guided Semantic Segmentation Network for High
Dimensional Multi-Scale Land Remote Sensing.- Reversible Data Hiding for
Encrypted 3D Mesh Model Based on Optimal Grouping Strategy and Multiple-Bit
Plane Prediction.- Semantic-Driven Free-View 3D Human Motion Video
Composite.- RG-GS: Rasterization-Enhanced and Geometric-Guided Gaussian
Splatting.- MoT: A Mixture of TriPlanes Framework for Frequency-Aware Dynamic
Neural Radiance Fields.- High Quality 3D Gaussian Avatar Modeling.- Content
Adaptive Light Field Representation Using Fourier Disparity Layers.- Research
on Legal Question Answering System with Retrieval-Augmented Large Language
Models.- Joint Source-Channel Coding with Large Language Model:
A Vibrotactile Example.- Persona Extraction and Integration with Large
Language Models Towards Personalized Dialogues.- MSBA: Adaptive Multi-Stream
Data Transmission Method with Bandwidth Awareness for End-Cloud
Systems.-Fabric Defect Detection Method Based on Unlabeled Compact
Deep Learning.- Causal Imitation Learning-Based Navigation Algorithm for
Drones.- Memory-Guided Hierarchical Feature Reconstruction for
Multi-class Unsupervised Anomaly Detection.- A Method for Surface Defect
Detection Based on Denoising and Self-Supervised Reconstruction.-
Transmission Line Bolt Missing Detection Based on Improved YOLOv8 Network.- A
Lightweight Infrared and Visible Image Fusion Method for Object Detection.-
MSO-YOLO: Real-Time Pedestrian Detection Algorithm on Multi-Scale and
Occlusion Situation.- Implicit Online Saddle Point Optimization.- MAFNet:
Multi-Attention Fusion Network for Infrared Small Target
Detection.- Personalized Federated Meta-Learning Based on Gradient
Clustering and Aggregation.- FMS-YOLO: Lightweight High-Altitude Work Safety
Belt Detection.- Ink Animation Creation via Human-AI Collaboration.- A
Meta-Space Architecture and Methods for Mobile Robot Inspection Digital Twin
System.- Predict Pedestrian Flow in Open Street Environment.- VNNet: A Deep
Learning-Based System for Video Visual Style Classification.