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Lesion detection on plant leaves is a critical task in plant pathology andagricultural research. Identifying lesions enables assessing the severity ofplant diseases and making informed decisions regarding disease control measuresand treatment strategies. To detect lesions, there are studies that proposewell-known object detectors. However, training object detectors to detect smallobjects such as lesions can be problematic. In this study, we propose a methodfor lesion detection on plant leaves utilizing class activation maps generatedby a ResNet-18 classifier. In the test set, we achieved a 0.45 success rate inpredicting the locations of lesions in leaves. Our study presents a novelapproach for lesion detection on plant leaves by utilizing CAMs generated by aResNet classifier while eliminating the need for a lesion annotation process.

Lesion Detection on Leaves using Class Activation Maps