• R. Sai Sreeja
• T. Pavani

Plant diseases brought on by various pathogenic agents are the primary reason for the decline in the quality of agricultural productivity. One industry that significantly affects the way of living and financial standing of people is agriculture. incorrect administration results in agricultural produce losses. The plant's health is negatively impacted by diseases, which has an impact on its development. It is essential to monitor the development of the crop in order to ensure that there is little loss. A subset of deep learning called convolutional neural networks is primarily used for signal processing, picture segmentation, and image classification. The primary goal of the suggested work is to identify a solution to the detection issue of 38 different classes of plant diseases using the simplest method while utilizing the least amount of computing resources to produce superior results to the conventional models. deployment of the VGG16 training model. It is extremely difficult for farmers to identify and manage plant diseases. Early detection of plant diseases is crucial so that farmers can act appropriately and quickly to prevent future losses. Our strategy is centered on the use of image processing to identify plant diseases. By uploading a leaf photograph to the system, our suggested software will assist farmers in identifying plant illnesses. A set of algorithms built into the system can determine the disease type. A number of processing stages are applied to the user's input image in order to identify the disease, and software then provides the user with the results.

Image Segmentation, Image Pre-processing, feature extraction, convolutional neural network

"Plant Leaf Disease Detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.c488-c495, August-2023, Available :http://www.jetir.org/papers/JETIR2308257.pdf

"Plant Leaf Disease Detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppc488-c495, August-2023, Available at : http://www.jetir.org/papers/JETIR2308257.pdf