A Paradigm for Object Detection to Recognize and Classify Vehicles Using Computer Vision
Year of publication
2025
Authors
Pitkäkangas, Ville; Kaakinen, Heikki; Tuunainen, Tom; Isohanni, Olli; Jose, Mitha Rachel
Abstract
Computer vision has emerged as a game-changing technology in the mining industry, revolutionizing operations and unlocking various use case scenarios. With increased trade facilities, ports are recognized as one of the most diligent work environments globally. The applications of machine learning and computer vision in ports offer improved security, efficient container management, intelligent traffic management, predictive maintenance, automated operations, and environmental monitoring. These advancements contribute to streamlined processes, cost reduction, enhanced safety, and overall optimization in port environments. This study proposes an approach to detect and classify vehicles in a port during the wintertime in Finland using computer vision and machine learning methods. Due to the high variability between seasons, particularly winter and summer in Finland, there might be a need to categorize images by time of year. The study is developed as a model to detect and classify vehicles in the port area, and the port used in the study acts as an international hub for various trades and industries, including but not limited to chemistry and mining.
Show moreOrganizations and authors
Centria University of Applied Sciences
Isohanni Olli
Publication type
Publication format
Article
Parent publication type
Journal
Article type
Original article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A1 Journal article (refereed), original researchPublication channel information
Publisher
Volume
23
Issue
1
Pages
1 - 20
ISSN
Publication forum
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Fully open publication channel
License of the publisher’s version
CC BY NC ND
Self-archived
No
Other information
Fields of science
Computer and information sciences
Keywords
[object Object],[object Object],[object Object],[object Object]
Publication country
Jordan
Internationality of the publisher
International
Language
English
International co-publication
No
Co-publication with a company
No
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes