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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 14, ISSUE 4, APRIL 2025

Plant Leaf Disease Detection using CNN

Adarsh Shetty, Akshay Kumar, Sathish N P, Kruthi P

DOI: 10.17148/IJARCCE.2025.14410

Abstract: Early detection of plant diseases is essential for safeguarding crop health and enhancing agricultural productivity. Traditional methods relying on manual observation are often slow, inaccurate, and inefficient. This ponder proposes a unused approach utilizing Convolutional Neural Systems (CNNs) to consequently distinguish plant maladies, altogether upgrading speed and precision. The show is prepared on a comprehensive collection of pictures, covering both solid and infected plant clears out, driving to a tall discovery rate. By joining exchange learning, the framework can perform successfully indeed with constrained information. Planned to function in real-time and at scale, this device is available to agriculturists, advertising a viable arrangement that diminishes the require for pesticides, bolsters way better trim administration, and empowers more feasible rural hones.

How to Cite:

[1] Adarsh Shetty, Akshay Kumar, Sathish N P, Kruthi P, “Plant Leaf Disease Detection using CNN,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14410