Modified ResNet-101 Model for Enhancing Classification of Leukemia White Blood Cell Images
Abhishek Choubey, D. Bharath, Gurram Manish Reddy, K. Shekar, Shruti Bhargava Choubey, Saket Gumudavelli · 2024
Deep learning techniques will help classify and better identify acute lymphoblastic leukemia (ALL). The study aims to make tests more accurate and faster by using a light Modified ResNet-101 model and new ways to identify things like Yolo V5 and Yolo V8. The deep learning method is being used in the article to fix common problems in classification, such as slow convergence and poor generalization. Evaluation tools, such as the F1-score, accuracy, precision, and memory, are used to rate hoy well a model works. The proposed Modified ResNet-101 model correctly identified Acute Lymphoblastic Leukemia (ALL) cells 98.1 % of the time, which is better than most transfer learning models. Even better results are seen when Yolo V5 and Yolo V8 are used to find diseases.