cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Vita Lystianingrum
Contact Email
jaree@its.ac.id
Phone
+6231-5947302
Journal Mail Official
jaree@its.ac.id
Editorial Address
Sekretariat JAREE Departemen Teknik Elektro Gedung B, Kampus ITS Sukolilo Surabaya 60111
Location
Kota surabaya,
Jawa timur
INDONESIA
JAREE (Journal on Advanced Research in Electrical Engineering)
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 25796216     DOI : https://doi.org/10.12962/j25796216.v4.i2.116
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
JAREE is an Open Access Journal published by the Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya – Indonesia. Published twice a year every April and October, JAREE welcomes research papers with topics including power and energy systems, telecommunications and signal processing, electronics, biomedical engineering, control systems engineering, as well as computing and information technology.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 11 Documents
 1   2 
Search results for , issue "Vol 6, No 2 (2022): October" : 11 Documents clear
Obstacle Detection Using Monocular Camera with Mask R-CNN Method Ari Santoso; Rafif Artono Darmawan; Mohamad Abdul Hady; Ali Fatoni
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.325

Abstract

An autonomous car is a car that can operate without being controlled by humans. Autonomous cars must be able to detect obstacles so that the car does not hit objects that are on the path to be traversed. Therefore, it takes a variety of sensors to determine the surrounding conditions. The sensors commonly used in autonomous cars are cameras and LiDAR. Compared to LiDAR, the camera has a relatively long detection distance, lower cost, and can be used to classify objects. In this final project, the monocular camera and Mask R-CNN algorithm are used to create a system that can detect obstacles in the form of cars, motorcycles, and humans. The system will generate segmentation instances, bounding boxes, classifications, distance, and width estimation for each detected object. By using a custom dataset that is created manually it fits perfectly with the surrounding environment. The system used can produce a Mean Average Precision of 0.81, a Mean Average Recall of 0.89, an F1 score of 0.86, and a Mean Absolute Percentage Error of 13.4% for the distance estimator. The average detection speed of each image is 0.29 seconds.

Page 2 of 2 | Total Record : 11

 1   2 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol 7, No 2 (2023): July Vol 7, No 1 (2023): January Vol 6, No 2 (2022): October Vol 6, No 1 (2022): April Vol 5, No 2 (2021): October Vol 5, No 1 (2021): April Vol 4, No 2 (2020): October Vol 4, No 1 (2020): April Vol 3, No 2 (2019): October Vol 3, No 1 (2019): April Vol 2, No 2 (2018): October Vol 2, No 1 (2018): April Vol 1, No 2 (2017): October Vol 1, No 1 (2017): April More Issue