Research Article
Deep Learning with Taxonomic Loss for Plant Identification
Table 2
Accuracies of eight state-of-the-art neural networks trained by cross-entropy and taxonomic loss on PlantCLEF 2015 dataset.
| Neural network | Loss function | Accuracy (%) | Family | Genus | Species |
| GoogLeNet [13] | CL | 72.62 | 65.97 | 59.69 | TAX | 74.95 | 68.07 | 61.06 |
| ResNet-50 [23] | CL | 77.48 | 71.59 | 65.07 | TAX | 78.55 | 72.20 | 65.15 |
| Inception-v3 [14] | CL | 77.93 | 74.01 | 67.98 | TAX | 80.31 | 74.46 | 67.42 |
| Inception-ResNet-v2 [11] | CL | 80.66 | 74.57 | 67.93 | TAX | 83.36 | 76.85 | 70.38 |
| MobileNet v2 [24] | CL | 72.13 | 65.65 | 59.16 | TAX | 74.18 | 67.52 | 60.42 |
| ShuffleNet v2 [25] | CL | 66.39 | 59.32 | 52.88 | TAX | 68.80 | 61.45 | 54.18 |
| DenSeNet-169 [26] | CL | 78.57 | 73.00 | 66.76 | TAX | 80.11 | 74.48 | 67.23 |
| SENet-154 [27] | CL | 81.25 | 76.81 | 70.08 | TAX | 83.19 | 78.08 | 71.15 |
|
|