DETECTION OF DISEASES IN TOMATO PLANTS USING DEEP LEARNING
Main Article Content
Abstract
Crop disease is increasingly becoming a concern for the farmers due to many factors such as climate change, growing resistance of pathogens, etc. An ill-diagnosed disease, leading to incorrect treatment ultimately affects the qualityand quantity of yield, thereby causing financial distress to the farmer. The proposed system aims to serve as a tool for the farmers to identify diseases in tomato plants, using a smartphone application as a means of interface and a Convolutional Neural Network (CNN) for identification of diseases. Processing and storage constraints are eliminated with the use of Cloud platform. We also aim to make the application more comprehensive by suggesting the remedies and preventive measures for the detected disease. The proposed system is highly scalable and aims at achieving a higher accuracy in disease detection by surveying the drawbacks of the existing system.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).
You are free to:
- Share — copy and redistribute the material in any medium or format
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes .
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
Rights of Authors
Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.