An enhanced classification of bacteria pathogen on microscopy images using deep learning

Son Ali, Akbar and Kamarul Hawari, Ghazali and Habsah, Hasan and Zeehaida, Mohamed and Wahyu Sapto, Aji (2021) An enhanced classification of bacteria pathogen on microscopy images using deep learning. In: 4th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2021 , 16 December 2021 , Virtual, Yogyakarta. 119 -123.. ISBN 978-166540151-7

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Abstract

Classification of bacteria pathogens has significant importance issues in the clinical microbiology field. The taxonomy identification of bacteria is usually recognized through microscopy imaging. The classical procedure has the lacks detection and a high misclassification rate. Recently, computer-aided detection is an applied deep learning approach that has been growing to improve classification quality. This study proposed an enhanced classification technique to recognize the bacterial pathogen images. The DensNet201 pre-trained CNN architecture has been used for deep feature extraction and classification. In addition, the transfer learning with the freeze layer technique applied can enhance the accuracy performance and reduce the false-positive rate. The experimental result can improve state-of-the-art decision-making.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Bacterial pathogen; CNN; Deep learning; Image classification; Transfer learning
Subjects:	Q Science > QH Natural history R Medicine > RB Pathology T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	27 Jun 2023 03:40
Last Modified:	27 Jun 2023 03:40
URI:	http://umpir.ump.edu.my/id/eprint/37877
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