Thai Herb Identification with Medicinal Properties Using Convolutional Neural Network


  • Lawankorn Mookdarsanit Business Computer Department, Faculty of Management Science, Chandrakasem Rajabhat University
  • Pakpoom Mookdarsanit Computer Science Department, Faculty of Science, Chandrakasem Rajabhat University


Herb Identification, Leaf Recognition, Convolutional Neural Network, VGGNet, Fast R-CNN


This paper builds an intelligent computer model to identify Thai herb from a single image using convolutional neural network. Since Thailand is one of the world herbal source. We used 2,700 herbal images with their medicinal properties to train the computer model that covered 11 well-known Thai herbs: Siamese Rough-bush, Cumin, Holy Basil, Sweet Basil, Cha Muang, Kaffir-lime Leaf, Siamese Morning-glory, Pandanus Leaf, Mint, Chinese Kale and Chaplu, respectively. The feature extraction framework and model architecture were done by Fast Region Convolution Neural Network (Fast R-CNN) and Visual Geometry Group Network (VGGNet) that produce the recall as higher than 0.75 and the precision as higher than 0.80.


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How to Cite

Mookdarsanit, L. ., & Mookdarsanit, P. . (2022). Thai Herb Identification with Medicinal Properties Using Convolutional Neural Network. Suan Sunandha Science and Technology Journal, 6(2), 34–40. Retrieved from



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