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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 12, ISSUE 6, JUNE 2023

Detection of Okra Disease

Shraddha C, Maanyatha M, Suloni Praveen, Supriya T C, Swathi Meghana K R

DOI: 10.17148/IJARCCE.2023.12630

Abstract: The okra crop, commonly called lady’s finger, is a commercial crop grown by farmers. But when these crops are infected, they wreak havoc on the life of farmers as well as on the economy. Plant disease issues are due to problems arising in agricultural activities and climate change. It causes money problems and losses to profits, farmers, and to whole industry depending on okra. If disease identification is done without appropriate techniques, then the problem remains the same. Various research has proposed several techniques to overcome these infections. CNN, Deep learning, and many other machine-learning techniques are used for detecting and classifying plant diseases.

Keywords: Okra, CNN, Deep learning, Machine learning, detecting, classifying

How to Cite:

[1] Shraddha C, Maanyatha M, Suloni Praveen, Supriya T C, Swathi Meghana K R, “Detection of Okra Disease,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12630