Please use this identifier to cite or link to this item: https://has.hcu.ac.th/jspui/handle/123456789/3511
Title: Which one is Kaphrao? Identify Thai Herbs with Similar Leaf Structure using Transfer Learning of Deep Convolutional Neural Networks
Authors: Sila Temsiririrkkul
Prarinya Siritanawan
Rungravi Temsiririrkkul
ศิลา เต็มศิริฤกษ์กุล
รุ่งระวี เต็มศิริฤกษ์กุล
Huachiew Chalermprakiet University. Faculty of Science and Technology
Japan Advanced Institute of Science and Technology. School of Information Science
Thammasat University. Faculty of Pharmacy
Keywords: Deep learning (Machine learning)
การเรียนรู้เชิงลึก (การเรียนรู้ของเครื่อง)
Image processing
การประมวลผลภาพ
Plants – Classification
พืช – การจำแนก
Herbs – Thailand
สมุนไพร – ไทย
Convolutional Neural Network
โครงข่ายประสาทเทียมแบบสังวัตนาการ
Neural networks (Computer science)
นิวรัลเน็ตเวิร์ค (วิทยาการคอมพิวเตอร์)
Convolutions (Mathematics)
คอนโวลูชัน (คณิตศาสตร์)
Image analysis
การวิเคราะห์ข้อมูลภาพ
Issue Date: 2021
Abstract: The recent Deep Learning algorithms have demonstrated incredible performance in many fields of research, especially an object detection task where algorithm advances are at a level that can be applied to real-world problems. Classification of plants by leaf image is one of the problems that has been of interest among computer vision researchers for a long time because of its challenges due to a large number of species and their complex features. There are many approaches presented and show promising performance for the task. However, in the tropical area where the diversity of plants is rich, examples of the physical similarity of the leaves in different species can be found easily. Moreover, it is reported that many accidents of misidentifying plants and their usages can be life-threatening. Thus, specimens of plants with similar leaf structures are interested in this research. We present a method to identify plants that are similar in morphological characters of leaf. Using image processing and deep learning techniques and transfer learning of several deep convolutional neural network architectures: VGG-16, ResNet-50, and InceptionV3, the proposed method can identify seven Lamiaceae plants yielded high accuracy prediction of 98.71%, 91.32%, and 98.17%, respectively.
Description: TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON), Auckland, New Zealand, 2021, pp. 738-743, doi: 10.1109/TENCON54134.2021.9707324
สามารถเข้าถึงบทความฉบับเต็ม (Full Text) ได้ที่ : https://ieeexplore.ieee.org/document/9707324
URI: https://has.hcu.ac.th/jspui/handle/123456789/3511
Appears in Collections:Science and Technology - Proceeding Document



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