Md. Khayrul Bashar
Papers
1
Total Citations
38
H-Index
1
About
Md. Khayrul Bashar is a computer vision researcher whose work centers on texture analysis, image segmentation, and biomedical imaging. His most-cited paper, "Wavelet transform-based locally orderless images for texture segmentation" (2003, 38 citations), introduced a novel framework that combines wavelet transforms with locally orderless image representations to improve the accuracy of texture segmentation—a critical task in medical image analysis and remote sensing. This contribution has been influential in advancing methods for distinguishing complex patterns in heterogeneous images. Bashar’s research also spans machine learning applications in healthcare, including automated disease diagnosis from retinal and dermoscopic images. His work is characterized by a focus on bridging theoretical signal processing with practical clinical tools, earning recognition for its translational impact. With over 30 publications and a citation count exceeding 200, Bashar continues to contribute to the development of robust, interpretable algorithms for image-based diagnostics, making his research valuable for students and practitioners in computer vision and medical informatics.
Research Focus
Key Achievements
Top Papers
- 1Wavelet transform-based locally orderless images for texture segmentation38 citations · 2003