Identification of Various Diseases in Plant Leaves Using Image Processing and CNN Approach
Diksha Tandekar, Snehlata Dongre
Abstract
India is an agricultural country with a population that depends on agriculture for about 70% of their income. Finding plant diseases is a crucial duty carried out in agriculture. Early plant disease detection is essential since it can stop additional harm to the crops. Plant leaf disease detection enables early identification and management of diseases in plants that can significantly impact crop health and yield. The subject of detecting plant diseases has undergone a revolution thanks to developments in this area. Visual inspection, spectral analysis, DNA-based, IOT-based, and automated image analysis are some of the cutting-edge methods used to find plant leaf diseases. This work focuses on the detection of diseases in leaves by using various deep learning techniques like VGG Net 19 and CNN. The accuracy of the models was found to be 85.4% and 83% respectively. The proposed work detects the diseases in the plant leaves and provides remedies for those diseases.