My Academic CV

Research Interests
Computer Vision Machine Learning
Deep Learning Artificial intelligence
Undergraduate Thesis

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.