DETEKSI 9 OBJEK JANTUNG JANIN PADA PANDANGAN 4-CHAMBER MENGGUNAKAN ARSITEKTUR FASTER R-CNN

ANGGRAINI, LIA and Nurmaini, Siti (2021) DETEKSI 9 OBJEK JANTUNG JANIN PADA PANDANGAN 4-CHAMBER MENGGUNAKAN ARSITEKTUR FASTER R-CNN. Undergraduate thesis, Sriwijaya University.

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Abstract

The heart is a vital organ and the center of the circulatory system in the human body. The appearance of the four-chamber and outflow tracts of the heart is considered an identifying marker that allows detecting the presence of the fetal heart. This study refers to the view of the four-chamber of the heart, the valves and the aorta. In the detection process, there are several methods that can generally be used to extract the features of all objects in the input image. Faster R-CNN is a method of deep learning which commonly used to detect an object of digital image in real-time. Faster R-CNN architecture consisted of the form of Fast R-CNN and RPN. The best model is obtained by adjusting the learning rate, epoch and batch size. The results were obtained with an mAP value of 90.22% and 93.79% for nine�object and five-object, respectively.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Objek, Jantung Janin, Ultrasonografi, Faster Region based Convolutional Neural Network
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:	Lia Anggraini
Date Deposited:	25 Aug 2021 06:35
Last Modified:	25 Aug 2021 06:35
URI:	http://repository.unsri.ac.id/id/eprint/52646

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