International Journal of Computing, Programming and Database Management

P-ISSN: 2707-6636, E-ISSN: 2707-6644
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2020, Vol. 1, Issue 2, Part A

Flower disease identification and classification by deep learning


Author(s): Rekha Paluru

Abstract: In India, Agriculture performs a crucial role because of the rapid increase of population and extended in demand for food. Therefore, it desires to increase crop yield. One major impact on low crop yield is an ailment caused by bacteria, viruses, and fungus. It can be avoided by the usage of plant disease detection strategies. Machine gaining knowledge of methods can be used for disease identification because it mainly practices on the information themselves and gives precedence to the outcomes of the sure task. This paper presents the levels of widespread flower illness detection systems and comparative study on gadgets getting to know classification strategies for flower disorder detection. In this survey, it located that Convolutional Neural Network offers high accuracy and detects an extra range of sicknesses.

DOI: 10.33545/27076636.2020.v1.i2a.15

Pages: 32-34 | Views: 602 | Downloads: 172

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International Journal of Computing, Programming and Database Management
How to cite this article:
Rekha Paluru. Flower disease identification and classification by deep learning. Int J Comput Programming Database Manage 2020;1(2):32-34. DOI: 10.33545/27076636.2020.v1.i2a.15
International Journal of Computing, Programming and Database Management

International Journal of Computing, Programming and Database Management

International Journal of Computing, Programming and Database Management
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