Paper Key : IRJ************368
Author: Faizal Ahmed.h,Rajeshwari.p
Date Published: 11 Nov 2023
Abstract
Exploring the detection algorithms on leaf images, this paper addresses the complexity of various tomato diseases and pests, which pose significant challenges in their pathology. Manual identification alone proves to be both difficult and error-prone. To overcome these issues, the paper focuses on the ten most prevalent tomato diseases and pests found in China. It constructs a convolutional neural network model utilizing VGG16 and transfer learning techniques. The training of this detection model is carried out using the KerasTensorFlow deep learning framework. Impressively, the model achieves an average classification accuracy of 89%.
DOI LINK : 10.56726/IRJMETS45370 https://www.doi.org/10.56726/IRJMETS45370