SEGMENTASI CITRA JANTUNG ANAK MENGGUNAKAN METODE YOLO

OKTARIAN, M. RENALDI and Nurmaini, Siti (2024) SEGMENTASI CITRA JANTUNG ANAK MENGGUNAKAN METODE YOLO. Undergraduate thesis, Sriwijaya University.

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Abstract

Child heart image segmentation is a crucial step in medical analysis for the diagnosis of heart diseases. In this study, we utilize the You Only Look Once (YOLO) method for the segmentation of child heart images. YOLO is a well known deep learning model in object detection due to its ability to perform real time detection with high accuracy. We collected a dataset of child heart images, performed manual annotation, and trained the YOLO model for segmentation. The performance of the model was evaluated using the Mean Average Precision (mAP) metric, with results indicating that this method is effective for child heart image segmentation. This model is expected to assist in the faster and more accurate diagnosis of pediatric heart diseases. Keywords : Deep Learning, Infant Hearts, YOLO

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deep Learning, Infant Hearts, YOLO
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	M. Renaldi Oktarian
Date Deposited:	27 Aug 2024 02:43
Last Modified:	27 Aug 2024 02:43
URI:	http://repository.unsri.ac.id/id/eprint/156231

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