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INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Detection of Plant Diseases using ResNet50 V2
Authors
  Akshit Kansal,  Nipun Arora,  Tushar Maurya,  Vinit Kr. Agarwal,  Bijendra tyagi

Abstract
Plant disease, deterioration of a plant's normal state (living species) which interrupts, stresses or alters its vital functions. We cannot deny the contribution of agriculture productivity in the Indian economy. That is one of the reasons why plant disease identification plays a vital role in the field of agriculture. Agriculture mainly needs to identify which crop is contaminated. We're indirectly playing a part in improving crop quality with the aid of this research. It is a recognition system focused on deep learning that will support the Indian Economy. Digital crop colour analysis is important because colour change is a rewarding signal for crop health and production. Then it can be assessed using visual measurements and inexpensive crop colour. Artificial Neural Network (ANN), ResNet50 V2, Flask, Adam optimizer will be used in this article.

Keywords- Agricultural productivity, Flask, RelU, ResNet50 V2, Adam optimizer, Keras.
Publication Details
Unique Identification Number - IJEDR2101004
Page Number(s) - 24-30
Pubished in - Volume 9 | Issue 1 | January 2021
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Akshit Kansal,  Nipun Arora,  Tushar Maurya,  Vinit Kr. Agarwal,  Bijendra tyagi,   "Detection of Plant Diseases using ResNet50 V2", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.9, Issue 1, pp.24-30, January 2021, Available at :http://www.ijedr.org/papers/IJEDR2101004.pdf
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