Table 1 Datasets and labeling software in the 16 studies, A for Classical CNN framework, B for Improved CNN architecture, C for CNN-based semantic segmentation network, and D for Labeling Software.
From: Recent advances in plant disease severity assessment using convolutional neural networks
| Â | Ref. | Dataset category | Links or references to datasets |
|---|---|---|---|
A | Apple leaf black rot | https://plantvillage.psu.edu/ (PlantVillage) | |
Citrus leaf from PlantVillage and crowdAI | |||
Coffee leaf miner, rust, brown leaf spot (self-made) | |||
Cucumber leaves (self-made) | |||
Maize common rust | https://plantvillage.psu.edu/ (PlantVillage) | ||
Tea leaf blight (self-made) | |||
Tomato early blight | https://plantvillage.psu.edu/ (PlantVillage) | ||
Pear leaf spot, curl, and slug (self-made) | |||
Wheat spike blast (self-made) | |||
Wheat yellow rust (self-made) | |||
B | AI Challenger Global AI Contest | ||
AI Challenger Global AI Contest | |||
C | Coffee, soybean, and wheat leaves | ||
Potato late blight (self-made) | |||
Rice bacterial leaf (self-made) | |||
Wheat fusarium head blight (self-made) | |||
D | Â | LabelMe | |
LabelImg |
