Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi
Megantara, Nugraha Asthra
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Object Detection using YOLOv8 : A Systematic Review Megantara, Nugraha Asthra; Utami, Ema
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5081

Abstract

This study is a Systematic Literature Review (SLR) that comprehensively reviews the recent advances in YOLOv8-based object detection models and their implementations in various application fields, such as UAV aerial photography, fruit ripeness identification, road defect detection, forest fire smoke detection, and medical imaging. This study evaluates the performance of YOLOv8 based on precision, recall, F1-score, and mean average precision (mAP) metrics, and compares its advantages and limitations with previous YOLO versions and other object detection algorithms. Improvements in the YOLOv8 architecture, including attention mechanisms, improved feature extraction, and hyperparameter optimization, enable significant improvements in accuracy and computational efficiency, especially for small objects and low-light conditions. In addition, the integration of image enhancement techniques strengthens the model's performance in challenging environmental conditions. This study is expected to be an important reference for researchers and practitioners in developing YOLOv8-based object detection models for real-world applications.
Co-Authors Ema Utami