The Implementation of Machine Learning in the Search to Fight Plant Disease

Volume: 10 | Issue: 01 | Year 2024 | Subscription
International Journal of Image Processing and Pattern Recognition
Received Date: 12/04/2023
Acceptance Date: 01/04/2024
Published On: 2024-05-30
First Page: 25
Last Page: 34

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By: Mohit Batra and Neha Bathla

Abstract

The agriculture business loses money and time due to plant diseases. Diagnosing disease accurately takes skill and devotion. Infected plants may have spots or streaks of a different color on their leaves. Several fungal, bacterial, and viral species can also infect plants. Individual plant disease signs and indications are assessed. Neural network applications are growing. Recent research studies have determined how well machine learning reviews traditional plant disease diagnosis methods. Deep learning, a subset of machine learning, may increase plant disease identification accuracy with a convolutional neural network model.

Keywords: Machine learning, plant disease, detection, deep learning, convolutional neural network (CNN), accuracy parameter

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Citation:

How to cite this article: Mohit Batra and Neha Bathla, The Implementation of Machine Learning in the Search to Fight Plant Disease. International Journal of Image Processing and Pattern Recognition. 2024; 10(01): 25-34p.

How to cite this URL: Mohit Batra and Neha Bathla, The Implementation of Machine Learning in the Search to Fight Plant Disease. International Journal of Image Processing and Pattern Recognition. 2024; 10(01): 25-34p. Available from:https://journalspub.com/publication/ijippr-v10i01-5785/
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