9th International Conference, CVIP 2024, Chennai, India, December 19-21, 2024, Revised Selected Papers, Part VI Herausgegeben:Kakarla, Jagadeesh; Balasubramanian, R.; Murala, Subrahmanyam; Vipparthi, Santosh Kumar; Gupta, Deep
9th International Conference, CVIP 2024, Chennai, India, December 19-21, 2024, Revised Selected Papers, Part VI Herausgegeben:Kakarla, Jagadeesh; Balasubramanian, R.; Murala, Subrahmanyam; Vipparthi, Santosh Kumar; Gupta, Deep
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.
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.
Produktdetails
Produktdetails
Communications in Computer and Information Science 2478
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Inhaltsangabe
.- 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.
.- 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.
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