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Computer Vision and Image Processing: 9th International Conference, CVIP 2024, Chennai, India, December 1921, 2024, Revised Selected Papers, Part VI [Pehme köide]

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  • Formaat: Paperback / softback, 214 pages, kõrgus x laius: 235x155 mm, 79 Illustrations, color; 7 Illustrations, black and white; XXII, 214 p. 86 illus., 79 illus. in color., 1 Paperback / softback
  • Sari: Communications in Computer and Information Science 2478
  • Ilmumisaeg: 23-Aug-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031937023
  • ISBN-13: 9783031937026
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Computer Vision and Image Processing: 9th International Conference, CVIP 2024, Chennai, India, December 1921, 2024, Revised Selected Papers, Part VISuurem pilt
  • Formaat: Paperback / softback, 214 pages, kõrgus x laius: 235x155 mm, 79 Illustrations, color; 7 Illustrations, black and white; XXII, 214 p. 86 illus., 79 illus. in color., 1 Paperback / softback
  • Sari: Communications in Computer and Information Science 2478
  • Ilmumisaeg: 23-Aug-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031937023
  • ISBN-13: 9783031937026
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783031937026.html

The Six-volume proceedings set CCIS 2473 and 2478 constitutes the refereed proceedings of the 9th International Conference on Computer Vision and Image Processing, CVIP 2024, held in Chennai, India, during December 19–21, 2024.

The 178 full papers presented were carefully reviewed and selected from 647 submissions.The papers focus on various important and emerging topics in image processing, computer vision applications, deep learning, and machine learning techniques in the domain.

.- Do not look so locally to fish skins: Improved YOLOv7 for fish
disease detection with Transformers.
.- MDDAMFN: Mixed Dual-Direction Attention Mechanism to Enhance Facial
Expression.
.- A brief review of state-of-the-art classification methods on benchmark
Peripheral Blood Smears datasets.
.- Detection and Monocular Depth Estimation of Ghost Nets.
.- DiffMamba: Leveraging Mamba for Effective Fusion of Noise and Conditional
Features in Diffusion Models for Skin Lesion Segmentation.
.- UDC-Mamba: Deep State Space Model for Under Display Camera
Image Restoration.
.- Walking Direction Estimation using Silhouette and Skeletal
Representations.
.- Realizing GAN Potential for Image Generation and Image-To-Image
Translation Using Pix2Pix.
.- DSFF-Net: Depthwise Separable U-Net with Feature Fusion for Polyp
Segmentation towards Hardware Deployment.
.- Cattle Identification through Multi-Biometric Features and Edge Device.
.- Fast sparse SAR Image Reconstruction Using Sparsity Independent
Regularized Pursuit.
.- Space Varying Motion Blur Degradation Dataset and Model for
Semantic Segmentation.
.- Multi-class classification of Gastrointestinal Disease detection using
Vision Transformers.
.- MGC: Music Genre Classification Using a Hybrid CNN-LSTM Model with MFCC
Input.
.- DBTC-Net: Dual-Branch Transformer-CNN Network for Brain Tumor Segmentation.