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Herb leaves pattern recognition using digital microscope and deep learning

Rahman, Muhammad Ariff Azizul and Gunawan, Teddy Surya and Kartiwi, Mira (2019) Herb leaves pattern recognition using digital microscope and deep learning. In: International Conference on Universal Wellbeing (ICUW2019), 4 - 6 Dec 2019, Kuala Lumpur, Malaysia.

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Abstract

Herb leaves are not fully exploited for their benefits due to the problem arise from difficulties in identifying the type of plants. Visual-based pattern recognition via microscopic imaging provides high precision and accuracy for identification that easily outperforms the limitations of human perception. A three-class dataset of 255 leaf vein images - betel, noni and ortosiphon stamineus, were captured by a digital microscope was constructed as a training set for a visual-based pattern recognition system. A simple visual-based pattern recognition system was constructed by using MATLAB and deep learning. Transfer learning was applied on a pretrained VGG-16 network with a validation accuracy of 91.03%. Further fine-tuning was applied on the network resulting an increase of accuracy to 98.72%.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 5588/78345
Uncontrolled Keywords: Herb Leaves, Digital Microscope, Pattern Recognition, Deep Learning
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology

Kulliyyah of Information and Communication Technology > Department of Information System
Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 09 Mar 2020 10:57
Last Modified: 10 Jul 2020 15:07
URI: http://irep.iium.edu.my/id/eprint/78345

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