All research areas
Research
Image Processing
Signal recovery and enhancement where the pixels are the evidence.
Before a model sees an image, something has to make that image worth seeing. We work on the acquisition and restoration end: noise, artefacts, calibration, and the pre-processing that decides whether downstream vision succeeds.
What this looks like in practice
- Denoising, restoration, and super-resolution
- Segmentation and morphological analysis
- Medical and scientific imaging pipelines
- Registration and geometric correction
- Quantitative measurement from imagery
Related publications
- HybridADNet: A Multi-Paradigm Deep Learning Framework for Alzheimer's Disease Diagnosis from Brain MRIMd Mahmudul Hoque, Md Kawser Islam, Ohidujjaman, Abdullah Rakib Akand, Mahmudul Hasan · 2 September 2026
- HybridVirusNet: A Hybrid Detection–Classification Framework for Multi-Class Virus Identification in TEM ImagesMd Mahmudul Hoque · 2 September 2026
- HyConDViT-Net: A Vision-Based Hybrid Deep Learning Approach Integrating CNNs, Vision Transformers, and Detection Backbones for PCOS Detection from Ultrasound ImagingMd Kawser Islam, Md Mahmudul Hoque, Md. Saiful Islam, Md. Sourav Talukder, Abdullah Rakib Akand, Mahmudul Hasan · 2 September 2026