Table 3 Comparison of other state-of-the-art models on the open-source datasets
From: DWTFormer: a frequency-spatial features fusion model for tomato leaf disease identification
Datasets | References | Year | Samples | Models | Accuracy/% |
|---|---|---|---|---|---|
AI Challenger 2018 | [38] | 2024 | 50000 | ERCP-Net | 86.21 |
[39] | 2021 | 35861 | Inception-ResNet-v2 | 86.10 | |
[40] | 2022 | 35861 | ConvViT | 86.83 | |
[41] | 2021 | 35861 | DECA_ResNet | 86.35 | |
[42] | 2023 | 36379 | ResNet101+attention | 87.11 | |
– | – | 35861 | DWTFormer | 96.18 | |
PlantVillage | [43] | 2024 | 54306 | TC-MRSN | 99.59 |
[44] | 2023 | 54306 | Dise-Efficient | 99.71 | |
[40] | 2022 | 54306 | ConvViT | 99.84 | |
[41] | 2021 | 54306 | DECA_ResNet | 99.74 | |
[42] | 2023 | 54306 | ResNet101+attention | 99.82 | |
– | – | 54306 | DWTFormer | 99.89 |