ABSTRACT
Agriculture was a major contributor to the economies of developing countries. We must raise production for GDP to expand. Plant diseases cause massive productivity losses in agriculture every year. This problem can be solved by an automatic method which can be helpful for correctly identifying it on a large farm, at early stages of the sickness. We have proposed a model to classify leaf diseases. The MobileNetV2 architecture was employed based on a convolutional neural network. For mobile devices, MobileNetV2 is extremely useful. We collect a variety of leaves and our model can be put to the test on the validation set. This has a good accuracy rate. We strive to reduce leaf disease in our model As a result of this technique; the agricultural sector is now assisting farmers in classifying diseases. The main objective of our approach is to reduce harm to diseased plants, which can aid in production growth.
