From: Activity landscape image analysis using convolutional neural networks
Collection | RF | SVM | Metric | ||
---|---|---|---|---|---|
Canny | Sobel | Canny | Sobel | ||
1 | 0.48 ± 0.00 | 0.50 ± 0.01 | 0.52 ± 0.01 | 0.57 ± 0.01 | Accuracy |
0.48 ± 0.01 | 0.50 ± 0.01 | 0.52 ± 0.01 | 0.58 ± 0.01 | F1 | |
0.23 ± 0.01 | 0.26 ± 0.01 | 0.28 ± 0.02 | 0.36 ± 0.02 | MCC | |
2 | 0.44 ± 0.01 | 0.50 ± 0.01 | 0.50 ± 0.02 | 0.56 ± 0.01 | Accuracy |
0.45 ± 0.01 | 0.50 ± 0.01 | 0.50 ± 0.02 | 0.56 ± 0.01 | F1 | |
0.16 ± 0.02 | 0.25 ± 0.02 | 0.25 ± 0.02 | 0.34 ± 0.02 | MCC | |
3 | 0.45 ± 0.01 | 0.49 ± 0.02 | 0.51 ± 0.02 | 0.56 ± 0.01 | Accuracy |
0.46 ± 0.01 | 0.49 ± 0.02 | 0.52 ± 0.02 | 0.57 ± 0.01 | F1 | |
0.18 ± 0.01 | 0.24 ± 0.02 | 0.27 ± 0.03 | 0.35 ± 0.02 | MCC | |
4 | 0.43 ± 0.01 | 0.54 ± 0.03 | 0.53 ± 0.04 | 0.60 ± 0.03 | Accuracy |
0.44 ± 0.02 | 0.54 ± 0.03 | 0.54 ± 0.04 | 0.60 ± 0.03 | F1 | |
0.16 ± 0.02 | 0.31 ± 0.05 | 0.30 ± 0.06 | 0.40 ± 0.04 | MCC | |
5 | 0.44 ± 0.02 | 0.50 ± 0.02 | 0.47 ± 0.03 | 0.55 ± 0.02 | Accuracy |
0.44 ± 0.02 | 0.51 ± 0.02 | 0.49 ± 0.03 | 0.57 ± 0.02 | F1 | |
0.16 ± 0.03 | 0.26 ± 0.04 | 0.21 ± 0.05 | 0.33 ± 0.03 | MCC | |
6 | 0.42 ± 0.01 | 0.50 ± 0.02 | 0.52 ± 0.03 | 0.56 ± 0.02 | Accuracy |
0.42 ± 0.01 | 0.51 ± 0.03 | 0.52 ± 0.02 | 0.58 ± 0.02 | F1 | |
0.13 ± 0.02 | 0.25 ± 0.04 | 0.28 ± 0.04 | 0.35 ± 0.03 | MCC | |
7 | 0.61 ± 0.01 | 0.66 ± 0.03 | 0.73 ± 0.02 | 0.74 ± 0.01 | Accuracy |
0.63 ± 0.01 | 0.66 ± 0.03 | 0.73 ± 0.02 | 0.74 ± 0.01 | F1 | |
0.42 ± 0.02 | 0.50 ± 0.04 | 0.59 ± 0.03 | 0.61 ± 0.01 | MCC |