Plant Leaf Disease Detection using Deep Learning

  • Anupam Bapat, Shubhadshraba Sabut, Kayal Vizhi

Abstract

    Plant Leaf diseases represent a significant risk to the sanitation framework, yield infections are a huge peril to sustenance security, yet their speedy conspicuous confirmation remains problematic in various bits of the world as a result of the nonattendance of the significant system.  The percentage of growing international Mobile phone selling in the market worldwide and latest development in computer imagery and prescient made it happening with the aid of deep getting to know has  progress the manner for telephone-assisted disorder prognosis. Using a dataset of 55,000 pictures of unhealthy as well as healthy, clean plant leaves recovered under controlled conditions, we will prepare  significant Convolutional neural network framework to recognize 14 gather species and 26 maladies(or nonattendance thereof). The readied model accomplishes an exactness of 99.35% on a lot of test arrangement, exhibiting the probability of this methodology. In general, the methodology of preparing profound learning models on progressively huge and openly accessible picture datasets presents a make way toward cell phone helped crop sickness finding on a monstrous worldwide scale.

Published
2020-05-07
How to Cite
Anupam Bapat, Shubhadshraba Sabut, Kayal Vizhi. (2020). Plant Leaf Disease Detection using Deep Learning. International Journal of Advanced Science and Technology, 29(06), 3599 - 3605. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/14162