ResViT-Rice: A Deep Learning Model Combining Residual Module and Transformer Encoder for Accurate Detection of Rice Diseases
Rice is a staple food for over half of the global population, but it faces significant yield losses: up to 52% due to leaf blast disease and brown spot diseases, respectively. This study aimed at proposing a hybrid architecture, namely ResViT-Rice, by taking advantage of both CNN and transformer for...
| Главные авторы: | , , , , |
|---|---|
| Формат: | Статья |
| Язык: | English |
| Опубликовано: |
MDPI AG
2023-06-01
|
| Серии: | Agriculture |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2077-0472/13/6/1264 |