Abstract
Agriculture provides a living for half of India's people. The infection in
crops poses a danger to food security, but quick detection is hard due to a lack of
facilities. Nowadays, Deep learning will automatically diagnose plant diseases from
raw image data. It assists the farmer in determining plant health, increasing
productivity, deciding whether pesticides are necessary, and so on. The potato leaf is
used in this study for analysis. Among the most devastating crop diseases is potato leaf
blight, which reduces the quantity and quality of potato yields, significantly influencing
both farmers and the agricultural industry as a whole. Potato leaves taken in the
research contain three categories, such as healthy, early blight, and late blight.
Convolution Neural Network (CNN), and Convolution Neural Network- Long Short
Term Memory(CNN-LSTM) are two neural network models employed to classify plant
diseases. Various performance evaluation approaches are utilized to determine the best
model.