Perbandingan Performa Model SSD Mobilenet V2 dan FPNLite dalam Deteksi Helm Pengendara Sepeda Motor

Setiawan, Dionisius Reinaldo Ananda and Riti, Yosefina Finsensia and Trisuwita, Nathanael Christian Perkasa (2024) Perbandingan Performa Model SSD Mobilenet V2 dan FPNLite dalam Deteksi Helm Pengendara Sepeda Motor. Komputika: Jurnal Sistem Komputer, 13 (1). pp. 131-138. ISSN 2252-9039 (print) | 2655-3198 (online)

	Text 13. Perbandingan Performa Model SSD Mobilenet V2 dan FPNLite dalam Deteksi Helm Pengendara Sepeda Motor.pdf Download (934kB)
	Text 13. HASIL SIMILARITY-YOSEFINA F RITI-PERBANDINGAN PERFORMA MODEL SSD MOBILENET V2 DAN FPNLITE.pdf Download (3MB)
	Text 13.[KORESPONDENSI] Perbandingan Performa Model SSD Mobilenet V2 dan FPNLite dalam Deteksi Helm Pengendara Sepeda Motor.pdf Download (1MB)

Abstract

One important aspect in computer vision is object detection, which aims to identify and determine the position of objects in images. In the context of safety, detecting helmet-wearing objects in motorcycle riders is crucial to reduce the risk of accidents and protect the riders. Helmets are the primary protective gear for motorcycle riders, safeguarding their heads from serious injuries during accidents. In this research, we implemented helmet object detection using the TensorFlow Framework with pre-trained models based on the Single Shot Multibox Detector (SSD) architecture, specifically the Mobilenet V2 and Mobilenet V2 FPNLite models. The Mobilenet V2 and Mobilenet V2 FPNLite models were trained using a dataset consisting of images of motorcycle riders wearing helmets and not wearing helmets. The performance evaluation results of both models using the mean Average Precision (mAP) metric showed that the proposed model achieved an mAP of 71.59% for the Mobilenet V2 FPNLite model and 80.12% for the Mobilenet V2 model.

Item Type:	Article
Uncontrolled Keywords:	Object Detection, Helmet, Tensorflow, SSD, Imagery
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Prodi Ilmu Informatika
Depositing User:	Yosefina Finsensia Riti
Date Deposited:	11 Mar 2025 07:53
Last Modified:	11 Mar 2025 07:53
URI:	http://repositori.ukdc.ac.id/id/eprint/2180

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