Table 6 Classification Accuracy of ALL Dataset in Train and Test Set for DDRNet Model.
From: An attention-based deep learning for acute lymphoblastic leukemia classification
Proposed modules | Landmark classification accuracy (%) | |
|---|---|---|
Train set | Test set | |
Convolution block | 95.37 | 84.30 |
Convolution + DRDB Block | 96.22 | 85.23 |
Convolution + DRDB + CSAB Block | 96.48 | 86.14 |
Convolution + GLFEB Block | 97.15 | 87.56 |
Convolution + GLFEB + CSAB Block | 97.39 | 87.98 |
Convolution + DRDB + GLFEB | 98.21 | 88.93 |
Convolution + DRDB + GLFEB + CSAB Block DDRNet | 99.86 | 91.98 |
