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All Journal Journal of Applied Electrical Engineering
Santonius, Santonius
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Control & Systems Engineering Electrical & Electronics Engineering

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Comparative Study of YOLOv5, YOLOv7 and YOLOv8 for Robust Outdoor Detection Wijaya, Ryan Satria; Santonius, Santonius; Wibisana, Anugerah; Jamzuri, Eko Rudiawan; Nugroho, Mochamad Ari Bagus
Journal of Applied Electrical Engineering Vol 8 No 1 (2024): JAEE, June 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v8i1.7207

Abstract

Object detection is one of the most popular applications among young people, especially among millennials and generation Z. The use of object detection has become widespread in various aspects of daily life, such as face recognition, traffic management, and autonomous vehicles. The use of object detection has expanded in various aspects of daily life, such as face recognition, traffic management, and autonomous vehicles. To perform object detection, large and complex datasets are required. Therefore, this research addresses what object detection algorithms are suitable for object detection. In this research, i will compare the performance of several algorithms that are popular among young people, such as YOLOv5, YOLOv7, and YOLOv8 models. By conducting several Experiment Results such as Detection Results, Distance Traveled Experiment Results, Confusion Matrix, and Experiment Results on Validation Dataset, I aim to provide insight into the advantages and disadvantages of these algorithms. This comparison will help young researchers choose the most suitable algorithm for their object detection task.
Co-Authors Jamzuri, Eko Rudiawan NUGROHO, MOCHAMAD ARI BAGUS Wibisana, Anugerah WIJAYA, RYAN SATRIA