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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

PLANT LEAF DISEASE DETECTION USING DEEP LEARNING

Harshitha M P, Meghana N, Dr H P Mohan Kumar

DOI: 10.17148/IJARCCE.2023.12644

Abstract: Agriculture must complete a huge effort that involves finding plant diseases. This is something that the economy is extremely dependent on. Due to the prevalence of plant illnesses, finding infections in plants is a crucial task in the agriculture industry. To detect illnesses in the leaves, and plant must be continuously examined. This constant inspection of the plants is labor-intensive and time-consuming since it involves many people. Simply said, some sort of deliberate strategy must be used to monitor the plants. The detection of Program-based diagnosis of diseases makes it easier to identify damaged leaves as well as save time and labour. The suggested method can more correctly categorise diseased plants by identifying their symptoms.

Keywords: In order to extract features from and categorization in plants disease species, CNN and deep learning techniques are used.

How to Cite:

[1] Harshitha M P, Meghana N, Dr H P Mohan Kumar, “PLANT LEAF DISEASE DETECTION USING DEEP LEARNING,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12644