Tripathi, Anshul, Chourasia, Uday, Dixit, Priyanka and Chang, Victor (2022). Plant Disease Detection Using Sequential Convolutional Neural Network. International Journal of Distributed Systems and Technologies, 13 (1),
Abstract
The main warning in the area of food preservation and care is on topmost are crop diseases. It has been recognized speedily, but it is not as easy as in any area of the world because no required framework exists. Both the healthy and diseased plant leaves were gathered and collected under the condition and circumstances. For this purpose, a public set of information was used. It was 20,639 images of plants that were infected and healthy. In order to recognize three different crops and 12 diseases, a sequential convolutional neural network from Keras was trained and applied. The perfection and exactness was 98.18 % onset of information of the above trained mentioned model using CNN . It has also indicated the probability and possibility of this strategy and procedure. The over-fitting occurs and neutralizes by putting the dropout value to 0.25.
Publication DOI: | https://doi.org/10.4018/ijdst.303672 |
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Divisions: | College of Business and Social Sciences > Aston Business School College of Business and Social Sciences > Aston Business School > Operations & Information Management |
Additional Information: | © The Authors. This AAM is licensed under a CC BY 4.0 license |
Uncontrolled Keywords: | Computer Networks and Communications,Hardware and Architecture |
Publication ISSN: | 1947-3540 |
Last Modified: | 06 Aug 2024 09:30 |
Date Deposited: | 26 Jul 2022 11:43 |
Full Text Link: | |
Related URLs: |
https://www.igi ... /article/303672
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2022-01-01 |
Accepted Date: | 2022-01-01 |
Authors: |
Tripathi, Anshul
Chourasia, Uday Dixit, Priyanka Chang, Victor ( ![]() |