UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 2
February-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1702058


Registration ID:
316142

Page Number

360-363

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Title

A review on :plant disease and pests detection using image processing and ANN

Abstract

According to the UN's Food and Agriculture Organization, global agriculture suffers annual losses of 20 to 40 percent (FAO). As a result, intelligent agriculture offers farmers the best option for eliminating these deadly insect pests by incorporating artificial intelligence methodologies with current ICT. Consequently, the production of their agriculture sector can be improved. Farmers and pesticide professionals will profit from this paper's ANN based approach to classifying pesticides automatically using artificial neural networks. Due to pest species' wide range of appearances, classifying them is far more difficult than classifying general objects, hence multi-class pest detection is a critical part of pest control that includes localization. Agriculture is one of the most important sources of income for the rural population. It has long been the most common practice. In ancient India, agriculture was done manually but the emerging technologies helped the farmers in order to improve crop production, income and reduce manpower. With the beneficiary of technologies there were many new problems encountered due to climatic events and natural disasters. One of them is pests, as pests are smaller in size and almost invisible to human eyes. Pest causes a lot of harm to crops and in order to safeguard the crops farmers use a large number of pesticides which harm crops and soil both. Several techniques haves been suggested till date for this reason, like symptoms such as spots are the best way to detect an insect. The color, size, and a number of these spots will also help in identifying the pest that has killed a plant.

Key Words

Pests Detection, AI, Artificial Neural Networks, Plant Disease Detection Using ANN

Cite This Article

"A review on :plant disease and pests detection using image processing and ANN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 2, page no.360-363, February-2017, Available :http://www.jetir.org/papers/JETIR1702058.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A review on :plant disease and pests detection using image processing and ANN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 2, page no. pp360-363, February-2017, Available at : http://www.jetir.org/papers/JETIR1702058.pdf

Publication Details

Published Paper ID: JETIR1702058
Registration ID: 316142
Published In: Volume 4 | Issue 2 | Year February-2017
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.28377
Page No: 360-363
Country: Alappuzha , Kerala , India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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