Table 5.
Misclassification rate.
| Model | Images Analyzed | Overall Misclassification Rate |
|---|---|---|
| DGN [51] | Digits 0 to 9 and combination (based on SVHN, and NORB sets) (realistic images) | 36.02% |
| Skip Deep Generative Model [52] | Digits 0 to 9 and combination (based on SVHN, and NORB sets) (realistic images) | 16.61% |
| GAN (feature matching) [48] | LSVRC2012 dataset with 1,000 categories (non-realistic images) | 8.11% |
| ALI [53] | 25 types of shapes (non-realistic images) | 7.42% |
| WGAN [40] | 6 classes of brain MR images (realistic images) | 50% |
| WGAN-GP [21] | 8 classes of florescent microscopy images (realistic images) | 6.9% |
| HEMIGEN (our approach) | Once cell, Two cells, Four cells (realistic images) | 12.3% |