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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
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