A Paradigm for Object Detection to Recognize and Classify Vehicles Using Computer Vision
Publiceringsår
2025
Upphovspersoner
Pitkäkangas, Ville; Kaakinen, Heikki; Tuunainen, Tom; Isohanni, Olli; Jose, Mitha Rachel
Abstrakt
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.
Visa merOrganisationer och upphovspersoner
Publikationstyp
Publikationsform
Artikel
Moderpublikationens typ
Tidning
Artikelstyp
En originalartikel
Målgrupp
VetenskapligKollegialt utvärderad
Kollegialt utvärderadUKM:s publikationstyp
A1 Originalartikel i en vetenskaplig tidskriftPublikationskanalens uppgifter
Förläggare
Volym
23
Nummer
1
Sidor
1 - 20
ISSN
Publikationsforum
Öppen tillgång
Öppen tillgänglighet i förläggarens tjänst
Ja
Öppen tillgång till publikationskanalen
Helt öppen publikationskanal
Licens för förläggarens version
CC BY NC ND
Parallellsparad
Nej
Övriga uppgifter
Vetenskapsområden
Data- och informationsvetenskap
Nyckelord
[object Object],[object Object],[object Object],[object Object]
Publiceringsland
Jordanien
Förlagets internationalitet
Internationell
Språk
engelska
Internationell sampublikation
Nej
Sampublikation med ett företag
Nej
Publikationen ingår i undervisnings- och kulturministeriets datainsamling
Ja