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Public Article
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    AGRICULTURAL CROP DISEASES DETECTION USING DEEP LEARNING TECHNIQUE: AN OVERVIEW

     
     
         
    ISSN: 2277 - 7601

    Publisher: author   

AGRICULTURAL CROP DISEASES DETECTION USING DEEP LEARNING TECHNIQUE: AN OVERVIEW
Indexed in Agriculture and Food Sciences
ARTICLE-FACTOR
 1.3
Article Basics Score: 3
Article Transparency Score: 3
Article Operation Score: 2
Article Articles Score: 2
Article Accessibility Score: 3
Article Problems
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article Flaws Reduces Credit

SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-0202
Publisher: Kiran Abasaheb More
Authors: P. Mercy Nesa Rani1, T. Rajesh2 And L. Hemochandra1
International Journal Address (IAA):
IAA.ZONE/2277388047601
eISSN : 2277 - 7601 VALID ISSN Validator
Abstract One of the important threats to food security is agricultural crop diseases wherein, quick diagnosis of plant diseases becomes difficult inmost of the countries in the world due to non-availability of domain experts at all times. Very recently, penetration of mobile phones andadvancement in computer technologies has made the diagnosis plant diseases on massive global scale easily to some extent. Moreover, theprogressive farmers can identify the plant diseases through the apps installed in their mobile phones. Among all these advancement incomputer technologies, the deep learning approach plays a crucial role in disease diagnosis and gives the clear cut idea towards the mobilephone assisted plant disease diagnosis in larger perspectives. This paper presents the basic concepts of artificial neural networks, its relatedreview of literature and a framework to diagnose the plant diseases effectively. This technique gives the knowledge to t...
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