| (Fuad et al., 2018) |
Aedes Aegypti
|
Google inception model |
99.77–99.98% accuracy, 0.21–5.13% cross-entropy error |
| (Azman & Sarlan, 2020) |
Aegypti, Albopictus, Anopheles, Armigeres, Culex
|
Convolution neural network |
0.7–73% accuracy |
| (Asmai et al., 2019) |
Aedes Aegypti
|
VGG16, VGG-19, ResNet-50, InceptionV3 |
77.31–85.10% accuracy, 0.31–0.66% loss |
| (Shang, Lin & Cong, 2020) |
Zebrafish
|
GoogLeNet, VGG-19, AlexNet |
91–100% accuracy |
| (Kakehi et al., 2021) |
Oyster |
coordinate system of PyTorch |
82.4% precision, 90.8% recall, 86.4% F-score |
| (Ong, Ahmad & Majid, 2021) |
House flies |
Convolution neural network |
88.44–92.95% precision, 88.23–94.10% recall, 87.56–92.89% accuracy, 88.08–93.02% F-score |
| Ours |
Zophobas Morio, Tenebrio Molitor
|
VGG-19, Inception v3 |
97.2% precision, 96.6% recall, 96.876% accuracy |
