Identification of Tomato Leaf Diseases Using Deep Convolutional Neural Networks

Author:

Singh Ganesh Bahadur1,Rani Rajneesh1ORCID,Sharma Nonita1,Kakkar Deepti1ORCID

Affiliation:

1. National Institute of Technology, Jalandhar, India

Abstract

Crop disease is a major issue now days; as it drastically reduces food production rate. Tomato is cultivated in major part of the world. The most common diseases that affect tomato crops are bacterial spot, early blight, septoria leaf spot, late blight, leaf mold, target spot, etc. In order to increase the production rate of tomato, early identification of diseases is highly required. The existing work contains very less accurate system for identification of tomato crop diseases. The goal of our work is to propose cost effective and efficient deep learning model inspired from Alexnet for identification of tomato crop diseases. To validate the performance of proposed model, experiments have also been done on standard pretrained models. The plantVillage dataset is used for the same, which contains 18,160 images of diseased and non-diseased tomato leaf. The disease identification accuracy of proposed model is compared with standard pretrained models and found that proposed model gave more promising results for tomato crop diseases identification.

Publisher

IGI Global

Subject

Information Systems

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Maize leaf disease detection using convolutional neural network: a mobile application based on pre-trained VGG16 architecture;New Zealand Journal of Crop and Horticultural Science;2024-08-04

2. Investigation of early symptoms of tomato leaf disorder by using analysing image and deep learning models;EAI Endorsed Transactions on Internet of Things;2024-01-10

3. Detection of crop disorder using deep learning;International Journal of Grid and Utility Computing;2024

4. Image‐based detection and classification of plant diseases using deep learning: State‐of‐the‐art review;Urban Agriculture & Regional Food Systems;2024-01

5. Classification of Tomato Leaf Disease using Feature Extraction with KNN Classifier;2023 Seventh International Conference on Image Information Processing (ICIIP);2023-11-22

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