CNN-based Indian medicinal leaf type identification and medical use recommendation
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 convoluti...
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| Veröffentlicht in: | Neural computing & applications 2024-04, Vol.36 (10), p.5399-5412 |
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| container_title | Neural computing & applications |
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| creator | Praveena, S. Pavithra, S. M. Kumar, A. Dalvin Vinoth Veeresha, P. |
| description | 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
%
. |
| doi_str_mv | 10.1007/s00521-023-09352-9 |
| format | Article |
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| subjects | Artificial Intelligence Artificial neural networks Classification Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer vision Data Mining and Knowledge Discovery Datasets Flowers & plants Herbal medicine Image processing Image Processing and Computer Vision Original Article Probability and Statistics in Computer Science |
| title | CNN-based Indian medicinal leaf type identification and medical use recommendation |
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