Table 7 Results using MobileNet.
From: Comprehensive brain tumour concealment utilizing peak valley filtering and deeplab segmentation
Epoch | Loss | Accuracy | Validation loss | Validation accuracy |
---|---|---|---|---|
1 | 10.5909 | 0.2944 | 3.1506 | 0.3706 |
2 | 3.0834 | 0.4543 | 1.5952 | 0.5584 |
3 | 1.8043 | 0.5406 | 1.2065 | 0.6041 |
4 | 1.2480 | 0.5964 | 0.8680 | 0.6954 |
5 | 0.8917 | 0.6599 | 0.6451 | 0.7843 |
6 | 0.7157 | 0.7589 | 0.5152 | 0.8020 |
7 | 0.5368 | 0.7995 | 0.5240 | 0.8122 |
8 | 0.5590 | 0.7716 | 0.4080 | 0.8528 |
9 | 0.4837 | 0.8173 | 0.3575 | 0.8680 |
10 | 0.3360 | 0.8731 | 0.3763 | 0.8604 |
11 | 0.3543 | 0.8655 | 0.5688 | 0.7665 |
12 | 0.3737 | 0.8579 | 0.3754 | 0.8350 |
13 | 0.3036 | 0.8782 | 0.2503 | 0.9264 |
14 | 0.3103 | 0.9061 | 0.3248 | 0.8731 |
15 | 0.2478 | 0.9010 | 0.2584 | 0.9137 |
16 | 0.2511 | 0.9061 | 0.1934 | 0.9239 |
17 | 0.2706 | 0.8959 | 0.2233 | 0.9264 |
18 | 0.1957 | 0.9340 | 0.2007 | 0.9315 |
19 | 0.1771 | 0.9416 | 0.1518 | 0.9569 |
20 | 0.1682 | 0.9391 | 0.1459 | 0.9619 |
21 | 0.1745 | 0.9518 | 0.2095 | 0.9289 |
22 | 0.1868 | 0.9162 | 0.1731 | 0.9340 |
23 | 0.1887 | 0.9543 | 0.1455 | 0.9518 |
24 | 0.1400 | 0.9594 | 0.1292 | 0.9594 |
25 | 0.1648 | 0.9416 | 0.1260 | 0.9645 |
26 | 0.1178 | 0.9721 | 0.0915 | 0.9797 |
27 | 0.1475 | 0.9645 | 0.1583 | 0.9442 |
28 | 0.2549 | 0.9061 | 0.1377 | 0.9594 |
29 | 0.1572 | 0.9492 | 0.1017 | 0.9746 |
30 | 0.1502 | 0.9518 | 0.1381 | 0.9176 |