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Chazhoor et al. Intell Robot 2022;2:1-19 https://dx.doi.org/10.20517/ir.2021.15 Page 13

Table 7. The mean training and validation accuracies and losses for MobileNet_v2 architecture for 20 epochs
Mean MobileNet_v2
Epoch
Training accuracy Validation accuracy Training loss Validation loss
1 0.55528 0.66322 1.12416 0.97572
2 0.64264 0.71714 0.94286 0.79604
3 0.6871 0.77108 0.806 0.77816
4 0.72912 0.7392 0.70786 0.89686
5 0.75566 0.74462 0.6542 0.8389
6 0.7858 0.78334 0.57576 0.75382
7 0.78846 0.7799 0.54498 0.86344
8 0.8392 0.83332 0.4141 0.62084
9 0.85942 0.8495 0.36976 0.57796
10 0.8649 0.85296 0.35118 0.57304
11 0.87458 0.84954 0.33336 0.57328
12 0.87606 0.85734 0.32184 0.5281
13 0.8768 0.86618 0.3207 0.50986
14 0.88106 0.84902 0.31194 0.545
15 0.88464 0.85344 0.30746 0.53638
16 0.88756 0.86178 0.2966 0.5141
17 0.88804 0.8613 0.30038 0.50172
18 0.88342 0.8608 0.30566 0.52828
19 0.88512 0.85688 0.30972 0.53054
20 0.8822 0.86176 0.31576 0.50632

Table 8. The mean training and validation accuracies and losses for DenseNet architecture for 20 epochs
Mean DenseNet
Epoch
Training accuracy Validation accuracy Training loss Validation loss
1 0.55724 0.6446 1.0884 1.04494
2 0.68426 0.73088 0.81858 0.74552
3 0.7488 0.72302 0.6718 1.14064
4 0.76168 0.75196 0.64602 0.90288
5 0.7874 0.79118 0.5675 0.69646
6 0.81936 0.76862 0.50594 0.85718
7 0.82216 0.77744 0.48568 0.76844
8 0.87188 0.79952 0.36034 0.66998
9 0.87814 0.83136 0.31836 0.51186
10 0.8911 0.80736 0.30766 0.5814
11 0.8954 0.82354 0.28282 0.58526
12 0.90164 0.83874 0.27306 0.59644
13 0.89908 0.8392 0.2748 0.5592
14 0.9019 0.84118 0.27446 0.57224
15 0.90704 0.83578 0.25116 0.5755
16 0.9096 0.84366 0.24786 0.5398
17 0.90582 0.84216 0.24938 0.5301
18 0.9063 0.84316 0.26094 0.60658
19 0.91196 0.8299 0.24698 0.57962
20 0.9079 0.84364 0.24388 0.52476