Tomato And Potato Leaf Disease Prediction With Health Benefits Using Deep Learning Techniques
K. Karthik, S. Rajaprakash, Shakil Ahmed, Rishan Perincheeri, C. Risho Alexander
Abstract
The main challenge to the farmers is that the weather, environmental factors cannot be predicted and controlled. Plant diseases also plays an important role in plant cultivation. Plant diseases are considered to be a major challenge to the farmers. As plant and leaf diseases is difficult to be identified with the naked eyes. To overcome this issue in the existing approach, the farmers periodically spray pesticides which might spoil the plants, crop failure. Thus, effective monitoring and identification of plant leaf disease detection at the early stage is essential to predict the leaf diseases and recommend preventive measures. The proposed system utilizes image processing with deep learning techniques to detect plant leaf diseases from potato and tomato datasets. Also, our proposed system could able to recommend the plant benefits helping the current generation of people with a common knowledge base along with plant leaf diseases prediction. For experimental results, this research uses jupyter tool with python script for performing plant leaf disease analysis.