Table 9 Training accuracy, training loss and test AUROC, accuracy and loss values obtained by the deep learning approaches for the 10 classes Dataset7
From: Deep learning based deep-sea automatic image enhancement and animal species classification
Classifier | Train accuracy | Train loss | Test AUROC | Test accuracy | Test loss |
|---|---|---|---|---|---|
CNN-1 | 0.5860 | 1.4096 | 0.6170 | 0.3124 | 2.4164 |
CNN-2 | 0.5314 | 1.6716 | 0.6370 | 0.3410 | 3.5452 |
CNN-3 | 0.9224 | 0.2387 | 0.8242 | 0.6749 | 1.9160 |
CNN-4 | 0.9552 | 0.1326 | 0.8136 | 0.6359 | 2.8140 |
DNN-1 | 0.5929 | 0.8642 | 0.8859 | 0.7944 | 1.2662 |
DNN-2 | 0.5813 | 0.9618 | 0.8864 | 0.7888 | 1.4685 |
DNN-3 | 0.5594 | 1.0097 | 0.8479 | 0.7299 | 0.8745 |
DNN-4 | 0.5626 | 0.9914 | 0.8760 | 0.7578 | 0.8389 |