ISSN 2394-5125
 

Research Article 


COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade.

Abstract
Plant identification is a very important task in the medicine industry. But, there is scarcity of botanists and it is not possible for a layman to do this work within time. Correct identification of the medicinal plants that go into the preparation of a medicine is also very crucial and leaves are one of the key elements to do so. Convolutional Neural Network, a technique in Deep Learning, takes an image as its input and recognizes various objects, setting importance to them and identifies one object from another. Considering other classification algorithms, image pre-processing requirements in a CNN are comparatively much lesser. In earlier methods, the features are manually engineered and worked upon, however with sufficient training CNN can also perform the same tasks more efficiently.
This paper gives information about comparison between various methods and their effectiveness in identifying medicinal leaves. This research proposes a method to identify plants from their leaves using CNNs. A comparison between three different ways of identifying these plants viz. a CNN model from scratch, the Tensorflow Object Detection API and Transfer Learning to train the model was made. Accordingly, the best model was selected with an accuracy of 98.2%, which would be used in future work to create an application for the same.

Key words: Convolutional Neural Networks, Object Detection, Transfer Learning, Indian Medicinal Plants, Deep Learning.


 
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How to Cite this Article
Pubmed Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. JCR. 2020; 7(19): 1219-1227. doi:10.31838/jcr.07.19.149


Web Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. http://www.jcreview.com/?mno=104129 [Access: July 17, 2020]. doi:10.31838/jcr.07.19.149


AMA (American Medical Association) Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. JCR. 2020; 7(19): 1219-1227. doi:10.31838/jcr.07.19.149



Vancouver/ICMJE Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. JCR. (2020), [cited July 17, 2020]; 7(19): 1219-1227. doi:10.31838/jcr.07.19.149



Harvard Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade (2020) COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. JCR, 7 (19), 1219-1227. doi:10.31838/jcr.07.19.149



Turabian Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. 2020. COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. Journal of Critical Reviews, 7 (19), 1219-1227. doi:10.31838/jcr.07.19.149



Chicago Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. "COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS." Journal of Critical Reviews 7 (2020), 1219-1227. doi:10.31838/jcr.07.19.149



MLA (The Modern Language Association) Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade. "COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS." Journal of Critical Reviews 7.19 (2020), 1219-1227. Print. doi:10.31838/jcr.07.19.149



APA (American Psychological Association) Style

Abhishek Gokhale, Anuradha Thakare, Sayali Babar, Srushti Gawade (2020) COMPUTATIONAL MODELS FOR IDENTIFYING INDIAN MEDICINAL PLANTS. Journal of Critical Reviews, 7 (19), 1219-1227. doi:10.31838/jcr.07.19.149





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