| 刊名 | Agricultural Biotechnology |
| 作者 | Peng QIN ，Nannan ZHANG， Rong WU， Lijun GAO |
| 作者单位 | llege of Information Engineering, Tarim University |
| DOI | DOI:10.19759/j.cnki.2164-4993.2023.05.018 |
| 年份 | 2023 |
| 刊期 | 5 |
| 页码 | 78-82 |
| 关键词 | Deep learning; Convolutional neural network; Apple disease identification; Southern Xinjiang; System implementation |
| 摘要 | Apple disease samples were collected from the southern Xinjiang and annotated to design a convolutional neural network model based on deep learning.The accuracy and robustness of the model was improved through training and optimization algorithms,and a complete apple disease identification system was developed with the model as the core,and evaluated for its performance in terms of accuracy,recall rate and speed.This study provides a reliable AI-based apple disease diagnosis solution for the apple planting industry in the southern Xinjiang,hoping to help farmers better manage and protect crop health. |
