Published Paper Details:

One of the main farming industries where the process of automating plants based on illnesses may be carried out is the agricultural industry. It's important to maintain track of healthy and diseased plant leaves in such an agricultural setting so that they may be further separated to produce exponential crop yields and returns. Utilizing picture categorization techniques, a variety of cutting-edge technologies have been combined for this goal, including machine learning, deep learning, and artificial intelligence. To accurately identify the presence of illness in plant leaves, deep learning-based models' working theories have been continually improving. We suggest using Convolutional Neural Network, ResNet-50, Efficient-B2, and VGG-16 for this purpose in order to identify and confirm the existence of plant illnesses in the relevant leaves. Gathering a dataset of 87k plant photos from the Kaggle library is how the paper is put into action. This library runs on 38 different categories and includes photographs of both healthy and sick plants. However, 250 photos from each class are used in the final implementation.