Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika
Hasibuan, Muhammad Haris
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Deep Neural Networks Approach for Monitoring Vehicles on the Highway Husein, Amir Mahmud; Christopher, Christopher; Gracia, Andy; Brandlee, Rio; Hasibuan, Muhammad Haris
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (760.998 KB) | DOI: 10.33395/sinkron.v4i2.10553

Abstract

Vehicle classification and detection aims to extract certain types of vehicle information from images or videos containing vehicles and is one of the important things in a smart transportation system. However, due to the different size of the vehicle, it became a challenge that directly and interested many researchers . In this paper, we compare YOLOv3's one-stage detection method with MobileNet-SSD for direct vehicle detection on a highway vehicle video dataset specifically recorded using two cellular devices on highway activities in Medan City, producing 42 videos, both methods evaluated based on Mean Average Precision (mAP) where YOLOv3 produces better accuracy of 81.9% compared to MobileNet-SSD at 67.9%, but the size of the resulting video file detection is greater. Mobilenet-SSD performs faster with smaller video output sizes, but it is difficult to detect small objects.
Co-Authors Amir Mahmud Husein, Amir Mahmud Brandlee, Rio Christopher Christopher Gracia, Andy