Classification of Plant disease and pesticides recommendation using Deep-Learning

被引:1
|
作者
Sadasivam, V. R. [1 ]
Suhail, S. Mohammed [1 ]
Rajan, M. Sowndar [1 ]
Tharun, R. [1 ]
机构
[1] KS Rangasamy Coll Technol, Dept Informat Technol, Tiruchengode, Tamilnadu, India
来源
JOURNAL OF POPULATION THERAPEUTICS AND CLINICAL PHARMACOLOGY | 2023年 / 30卷 / 06期
关键词
CNN; Plant Disease; Deep Learning;
D O I
10.47750/jptcp.2023.30.06.044
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
One of the primary reasons for failure of gather production and agriculture is the distinct discovery and confirmation of plant contaminations. The examination of any recognizable spots in any part of the plant helps us distinguish between two plants, in fact, any spots or assortment disguises. This is the examination of plant disease. One of the most important considerations for cultivating development is the plant's acceptability. It's obvious that it's hard to get the distinctive evidence of plant diseases right. The identification of the condition necessitates a significant amount of effort and authority, as well as stacks of data in the field of plants and analyses of the revelation of those conditions. As a result, picture dealing is utilized to identify plant contaminations. The picture acquisition, picture extraction, picture division, and picture pre-treatment procedures are followed by the disclosure of diseases. By taking pictures of their leaves, stems, and other natural objects, we will demonstrate in this paper how plants can reveal their health issues. In a similar vein, we will talk about how this project will be made and how picture pre- processing and extraction will be used.
引用
收藏
页码:E391 / E397
页数:7
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