Paper Title
Investigation on plant leaf diseases using machine learning
Article Identifiers
Authors
SRIMAYA MOHAPATRA
Keywords
Image processing, Deep learning, KNN, SVM.
Abstract
Disease diagnosis display an important character in better understanding the Indian financial system in terms of agricultural production. Many machine learning processes such as SVM (support vector machine), informal forest, KNN, Naïve Bayes, pruning trees, etc., are used to detect and distinguish plant illness. However, the development of machine learning with deep learning (DL) is intended to have a significant impact on improving accuracy. Deep learning may be a branch of computer science. The benefits of automatic learning and having a domain, are closely related to theoretical and industry company It is widely used in video and image enhancing, voice upgrading, and dialogue processing. The use of in-depth learning in the diagnosis of disease can intercept the deterioration generated by genetic alternatives, make the absorption of the disease a major goal, and improve the effectiveness of analysis and the pace of mechanical change. We hope that this work will be very helpful to researchers conducting research on plant and insect diseases.
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How To Cite (APA)
SRIMAYA MOHAPATRA (July-2024). Investigation on plant leaf diseases using machine learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), f1-f22. https://ijnrd.org/papers/IJNRD2407401.pdf
Issue
Volume 9 Issue 7, July-2024
Pages : f1-f22
Other Publication Details
Paper Reg. ID: IJNRD_225686
Published Paper Id: IJNRD2407401
Downloads: 000122003
Research Area: Engineering
Country: Raghunathpur, Odisha, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2407401.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407401
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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