Deep learning image-based automated application on classification of tomato leaf disease by pre-trained deep convolutional neural networks

oleh: ReddyPriya Madupuri, Dinesh Reddy Vemula, Anil Carie Chettupally, Abdur Rashid Sangi, Pallam Ravi

Format: Article
Diterbitkan: Mehran University of Engineering and Technology 2023-07-01

Deskripsi

The agriculture sector is one of the major sectors in India. India is well known for the production of various varieties of spices, fruits, vegetables, herbs, etc. Along with the pollution, the diseases that are affecting plants are increasing and there are various reasons for this. Tomato is one of the high-demand crops in the market and is produced in large quantities. There are many diseases that tomatoes get affected by because of the virus, fungus, bacteria, etc. In this project, we proposed a model to identify the diseases of tomato plants using images of tomato plant leaves. Our main goal is to develop a good model with decent accuracy and a mobile application that works with or without the internet for users, especially farmers. The Convolution Neural Network-based approach is used to create the model for this project. This proposed system model gives 98 % accuracy and that model is converted to the TF Lite model which is used in the application. This application can precisely predict the disease of the tomato leaf and suggest the treatment for it.