Table 7 Comparison of DDRNet with the state-of-the-art approaches.
From: An attention-based deep learning for acute lymphoblastic leukemia classification
Reference no | Dataset | Method | Accuracy (%) | Type |
|---|---|---|---|---|
RF and GLCM | 90.00 | Machine learning algorithm | ||
MLP, SVM, and Dempster-Shafer classifiers | 96.72 | |||
Amreek Clinical Laboratory Saidu Sharif Swat KP Pakistan | CNN | 97.78 | Deep learning techniques | |
ALLIDB1 and C NMC 2019 | YOLOv4 | 96.06 | ||
Proposed | Blood Cell Image14 | DDRNet | 99.86 | |
Leukemia Dataset(ISBI 2019)49 | 99.86 |
