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All Journal Jurnal Teknologi dan Manajemen Informatika
Kolandaisamy, Raenu
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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A Comparative Study of YOLOv8 and YOLO - NAS Performance in Human Detection Image Hendrawan, Nofrian Deny; Kolandaisamy, Raenu
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.12192

Abstract

In the realm of computer vision, object detection holds immense importance across applications such as surveillance and autonomous vehicles. This study addresses the critical challenge of human detection under low-light conditions, essential for nocturnal surveillance and autonomous driving systems. Focusing on the evolution of YOLO models, particularly YOLO - NAS and YOLOv8, a research gap is identified concerning their performance in low-light scenarios. The research conducts a detailed analysis of YOLO - NAS and YOLOv8 effectiveness in human detection under reduced ambient illumination. Object detection, vital in computer vision, faces challenges in low-light scenarios. This study concentrates on human detection due to its significance in night-time surveillance and autonomous driving. Despite YOLO models' evolution, a research gap exists in comparing their performance in low-light conditions. The study aims to fill this gap, providing insights for enhancing human detection methodologies in challenging lighting environments.
Co-Authors Hendrawan, Nofrian Deny