| dc.description.abstract | Because crop species, crop disease symptoms, and environmental conditions vary,
it might be difficult to detect potato leaf disease in its early stages. These elements
make it challenging to spot potato leaf diseases in their early stages. To identify
illnesses in potato leaves, numerous machine learning methods have been
developed. The existing technology, however, is unable to identify crop species or
crop diseases in general because these models are developed and evaluated using
images of plant leaves from a particular region. A multi-level deep learning model
for identifying potato leaf disease has been built in this study. Using the YOLOv5
image segmentation method, the first level of the algorithm extracts the potato leaves
from the image of the potato plant. | en_US |
