| breast-tumour-classification-on-pcam | DenseNet-121 (e) | #8 | AUC: 0.921 |
| classification-on-indl | DenseNet201 | #3 | Average Recall: 90.99% |
| crowd-counting-on-ucf-qnrf | Densenet201 | #15 | MAE: 163 |
| image-classification-on-cifar-10 | DenseNet (DenseNet-BC-190) | #105 | Percentage correct: 96.54 |
| image-classification-on-cifar-100 | DenseNet-BC | #92 | Percentage correct: 82.82 |
| image-classification-on-cifar-100 | DenseNet | #97 | Percentage correct: 82.62 |
| image-classification-on-gashissdb | DenseNet-169 | #8 | Accuracy: 96.90Precision: 99.91F1-Score: 98.38 |
| image-classification-on-imagenet | DenseNet-264 | #810 | Top 1 Accuracy: 77.85% |
| image-classification-on-imagenet | DenseNet-201 | #823 | Top 1 Accuracy: 77.42% |
| image-classification-on-imagenet | DenseNet-169 | #863 | Top 1 Accuracy: 76.2% |
| image-classification-on-imagenet | DenseNet-121 | #900 | Top 1 Accuracy: 74.98% |
| image-classification-on-svhn | DenseNet | #15 | Percentage error: 1.59 |
| medical-image-classification-on-nct-crc-he | DenseNet-169 | #5 | Accuracy (%): 94.41F1-Score: 96.90Precision: 99.87… |