ABSTRACT
Crop disease protection is important for global food security, while the recognition of crop diseases at early stage is the key part of disease protection. The traditional identification and detection of crop leaf diseases is carried out by agricultural technicians. The identification and diagnosis of crop leaf disease is of great significance to improve the quality of crop cultivation. Compared with the traditional manual diagnosis method, the automatic identification of crop leaf disease based on computer vision technology has high efficiency and no subjective judgment error. But the traditional image processing technology is affected by different illumination conditions, cross shading. The algorithm's robustness is affected. Because deep learning dose not need to set learning features manually, which greatly improves the recognition efficiency. This project is developed in matlab using image processing deep learning CNN algorithm.
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