Creating New Knowledge
My Academic CV
Research Interests
Undergraduate Thesis
Computer Vision | Machine Learning |
Deep Learning | Artificial intelligence |
Topic: Acute Lymphocytc Leukemia Recognition Using CNN
Supervisor: Dr. Md. Masudul Ahsan, Professor, Dept. of Computer Science and Engineering, KUET- Helps to detect blood cancer at an early stage, which leads to needing several methods, for example, microscopic color imaging, segmentation, classification, and localization.
- Segments WBC cells (accuracy: 90.25%), sends them to the CNN models to be recognized if it is a blast or normal cells (accuracy: 87%), and finally localizes the blast cells on the blood smear image.