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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 3, MARCH 2024

Tomato Leaf Disease Detection

N. Veeratharini, K. Swathi, R. Arthi

DOI: 10.17148/IJARCCE.2024.133139

Abstract: Agriculture is the backbone of nations, and safeguarding crops from diseases is vital for food security. This research focuses on tomato, a quintessential crop present in various culinary forms, emphasizing the importance of disease prevention for maintaining quality. This article presents an innovative approach utilizing Machine Learning algorithms for early prediction and detection of tomato plant leaf diseases. A curated datasets was prepared, and operations such as feature extraction and rigorous testing were performed on it using eight diverse machine learning algorithms

Keywords: machine learning algorithm, disease prevention, feature extraction Cite: N. Veeratharini, K. Swathi, R. Arthi, "Tomato Leaf Disease Detection", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133139.

How to Cite:

[1] N. Veeratharini, K. Swathi, R. Arthi, “Tomato Leaf Disease Detection,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.133139