Leaf Diseases Detection System Using Machine Learning
Abstract
Our country's main business is agriculture. The majority of people reside in rural regions and rely solely on agricultural products for their livelihood. The quality and yield of agricultural goods will decline in any plant that has the disease. Research and illness detection are therefore crucial. For disease to be successfully controlled and inhibited for practical cultivation and food preservation, genuine crop disease exposure and identification are essential. For farmers to succeed, early illness detection and diagnosis are essential.
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References
[2]Plant disease identification using machine learning. 2018 International Conference on Design Innovations for the 3Cs: Compute, Communicate, and Control. Ramesh, Shima, et al (ICDI3C). IEEE, 2018
[3] "A study on discovery and bracket of cotton splint conditions," 2016 International Conference on Electrical, Electronics, and Optimization ways( ICEEOT), pp. 2499 – 506, doi10.1109/ICEEOT.2016.7755143, B.S. Prajapati, V.K. Dabhi, andH.B. Prajapati. ( 10) 2018 9th IEEE Control and System Graduate Research Colloquium( ICSGRC), pp. 168 – 171, doi10.1109/ICSGRC.2018.8657603; N.M. Yusoff, I.S. Abdul Halim, N.E. Abdullah, and A.A. Ab Rahim," Real- time Hevea Leaves conditions Discovery using Sobel Edge Algorithm on FPGA A Preliminary Study."
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