Anass Garbaz

Orcid: 0000-0002-8526-3955

According to our database1, Anass Garbaz authored at least 11 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
HDEFG-UFormer: A Hierarchical Depthwise-Expanded Feature Grouping Transformer-Based UNet for Gastrointestinal Disease Segmentation.
IEEE Trans. Syst. Man Cybern. Syst., May, 2026

2025
Combined deep convolutional neural networks for abnormality classification in wireless capsule endoscopy images.
Multim. Tools Appl., October, 2025

GSAC-UFormer: Groupwise Self-Attention Convolutional Transformer-Based UNet for Medical Image Segmentation.
Cogn. Comput., February, 2025

MLFE-UNet: Multi-Level Feature Extraction Transformer-Based UNet for Gastrointestinal Disease Segmentation.
Int. J. Imaging Syst. Technol., January, 2025

XCC-Net: An X-Shaped Collective Convolution Network Architecture for Medical Image Segmentation.
Mach. Learn. Knowl. Extr., 2025

InCoLoTransNet: An Involution-Convolution and Locality Attention-Aware Transformer for Precise Colorectal Polyp Segmentation in GI Images.
J. Imaging Inform. Medicine, 2025

DMFC-UFormer: Depthwise multi-scale factorized convolution transformer-based UNet for medical image segmentation.
Biomed. Signal Process. Control., 2025

2024
UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images.
J. Imaging Inform. Medicine, 2024

Bleeding Segmentation Based on a U-Formed Network with Separable Contextual Feature-Guided in Wireless Capsule Endoscopy Images.
Proceedings of the 11th International Conference on Wireless Networks and Mobile Communications, 2024

2023
Bleeding Segmentation Based on a Bleeding Feature Engagement Module in Wireless Capsule Endoscopy.
Proceedings of the 17th International Conference on Signal-Image Technology & Internet-Based Systems, 2023

2022
Bleeding classification in Wireless Capsule Endoscopy Images based on Inception-ResNet-V2 and CNNs.
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2022


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