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Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning
Curcuma longa (turmeric) and Curcuma zanthorrhiza (temulawak) are members of the Zingiberaceae family that contain curcuminoids, essential oils, starch, protein, fat, cellulose, and minerals. The nutritional content proportion of turmeric is different from temulawak which implies differences in econ...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280267/ https://www.ncbi.nlm.nih.gov/pubmed/37346311 http://dx.doi.org/10.7717/peerj-cs.1168 |
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author | Pratondo, Agus Elfahmi, Elfahmi Novianty, Astri |
author_facet | Pratondo, Agus Elfahmi, Elfahmi Novianty, Astri |
author_sort | Pratondo, Agus |
collection | PubMed |
description | Curcuma longa (turmeric) and Curcuma zanthorrhiza (temulawak) are members of the Zingiberaceae family that contain curcuminoids, essential oils, starch, protein, fat, cellulose, and minerals. The nutritional content proportion of turmeric is different from temulawak which implies differences in economic value. However, only a few people who understand herbal plants, can identify the difference between them. This study aims to build a model that can distinguish between the two species of Zingiberaceae based on the image captured from a mobile phone camera. A collection of images consisting of both types of rhizomes are used to build a model through a learning process using transfer learning, specifically pre-trained VGG-19 and Inception V3 with ImageNet weight. Experimental results show that the accuracy rates of the models to classify the rhizomes are 92.43% and 94.29%, consecutively. These achievements are quite promising to be used in various practical use. |
format | Online Article Text |
id | pubmed-10280267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102802672023-06-21 Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning Pratondo, Agus Elfahmi, Elfahmi Novianty, Astri PeerJ Comput Sci Bioinformatics Curcuma longa (turmeric) and Curcuma zanthorrhiza (temulawak) are members of the Zingiberaceae family that contain curcuminoids, essential oils, starch, protein, fat, cellulose, and minerals. The nutritional content proportion of turmeric is different from temulawak which implies differences in economic value. However, only a few people who understand herbal plants, can identify the difference between them. This study aims to build a model that can distinguish between the two species of Zingiberaceae based on the image captured from a mobile phone camera. A collection of images consisting of both types of rhizomes are used to build a model through a learning process using transfer learning, specifically pre-trained VGG-19 and Inception V3 with ImageNet weight. Experimental results show that the accuracy rates of the models to classify the rhizomes are 92.43% and 94.29%, consecutively. These achievements are quite promising to be used in various practical use. PeerJ Inc. 2022-12-15 /pmc/articles/PMC10280267/ /pubmed/37346311 http://dx.doi.org/10.7717/peerj-cs.1168 Text en © 2022 Pratondo et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Pratondo, Agus Elfahmi, Elfahmi Novianty, Astri Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title | Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title_full | Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title_fullStr | Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title_full_unstemmed | Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title_short | Classification of Curcuma longa and Curcuma zanthorrhiza using transfer learning |
title_sort | classification of curcuma longa and curcuma zanthorrhiza using transfer learning |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280267/ https://www.ncbi.nlm.nih.gov/pubmed/37346311 http://dx.doi.org/10.7717/peerj-cs.1168 |
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