AppleLeafNet: a lightweight and efficient deep learning framework for diagnosing apple leaf diseases
Muhammad Umair Ali,
Majdi Khalid,
Majed Farrash
et al.
Abstract:Accurately identifying apple diseases is essential to control their spread and support the industry. Timely and precise detection is crucial for managing the spread of diseases, thereby improving the production and quality of apples. However, the development of algorithms for analyzing complex leaf images remains a significant challenge. Therefore, in this study, a lightweight deep learning model is designed from scratch to identify the apple leaf condition. The developed framework comprises two stages. First,… Show more
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