CNN-based Indian medicinal leaf type identification and medical use recommendation

被引:1
|
作者
Praveena, S. [1 ]
Pavithra, S. M. [1 ]
Kumar, A. Dalvin Vinoth [2 ]
Veeresha, P. [1 ]
机构
[1] CHRIST, Dept Math, Bengaluru 560029, India
[2] CHRIST, Dept Stat & Data Sci, Bengaluru 560029, India
来源
NEURAL COMPUTING & APPLICATIONS | 2024年 / 36卷 / 10期
关键词
Convolution neural network; Graphical user interface; Gradio; Confusion matrix;
D O I
10.1007/s00521-023-09352-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Medicinal leaves are playing a vital role in our everyday life. There are an enormous amount of species present in the world. Identification of each type would be a tedious task. Using image processing technology, we can overcome this problem by providing computer vision with the help of a convolution neural network (CNN). The objective of this research is to find out the best CNN model that helps in classifying the plant leaf species and identifying its category. In this research work, the proposed basic CNN model consisting of four convolution layers uses ten different medicinal leaf species each belonging to two categories providing an accuracy of 96.88%.
引用
收藏
页码:5399 / 5412
页数:14
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