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  Published Paper Details:

  Paper Title

A FRAMEWORK FOR LEAF DISEASE DETECTION

  Authors

  Rubina,  Sujatha P

  Keywords

A FRAMEWORK FOR LEAF DISEASE DETECTION

  Abstract


"Image processing is a form of signal processing for which input is an image, video frame or photograph". It deals with the computerized images with the assistance of an advanced PC. It additionally concentrates on execution preparing the image by building up the PC framework. Framework acknowledged the contribution as a computerized image and utilizing effective calculations the framework will handle the image, and gives a image as a yield.. Plant diseases are the primary wellspring of plant harm which bring about financial and generation misfortunes in agrarian ranges. Inferable from troubled climatic and ecological conditions, event of plant illnesses is on the ascent. There are different sorts of diseases in plants, assortment of side effects, for example, spots or smirch emerging on the plant leaves, seeds and stanches of the plant. Keeping in mind the end goal to deal with these elements viably, there is a need to present a programmed strategy for plant observation that can examine plant conditions and applied information-based answer for recognized and group different infections. Machine Learning is a characteristics proper structure to bolster this issue.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT1135627

  Paper ID - 266303

  Page Number(s) - 265-270

  Pubished in - Volume 6 | Issue 1 | January 2018

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Rubina,  Sujatha P,   "A FRAMEWORK FOR LEAF DISEASE DETECTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.6, Issue 1, pp.265-270, January 2018, Available at :http://www.ijcrt.org/papers/IJCRT1135627.pdf

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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
ISSN
ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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