A Review on Pomegranate Disease Classification Using Machine Learning and Image Segmentation Techniques

被引:0
|
作者
Kantale, Pooja [1 ]
Thakare, Shubhada [1 ]
机构
[1] Govt Coll Engn Amravati, Dept Elect Engn, Amravati, Maharashtra, India
关键词
Pomegranate diseases; Ensemble algorithm; PSO algorithm;
D O I
10.1109/iciccs48265.2020.9121161
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paramount motive of farming is to yield good crops without any disease present. The role of digital image processing along with image analysis is indispensable in the sector of agriculture. Preprogrammed awareness of plant malady and production of good plants is of substantial significance in agriculture industrialization. To prevent the loss of agricultural yield one has to recognize the malady. Manually, detection of plants malady is quite difficult, it required huge time for analyzing the malady present on the fruit. To tame this problem, a machine learning-based approach is recommended which can evaluate the image of the fruit to detect the disease. Image processing is the method which is successfully used for the recognition of plant malady. This paper, contribute a review on approach evolve for detection of diseases in plants using their images.
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页码:455 / 460
页数:6
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