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The difference of leaf disease images within the class is large but the difference between the class is small, so it is very important to represent the features of the local area of the target. Moreover, the complex network occupies a large amount of computer memory and wastes a large amount of computing resources, which is difficult to meet the needs of low-cost terminals. This paper proposes a fine-grained disease categorization method based on attention network to solve the problem. Indoi:10.1109/access.2022.3167513 fatcat:l6nxyhqopfagpfrxutrwqxw6mu