Pregled bibliografske jedinice broj: 1090598
UrTra2D – Urban Traffic 2D Object Detection Dataset
UrTra2D – Urban Traffic 2D Object Detection Dataset // Proceedings of 10th IEEE International Conference of Consumer Technology
Berlin, Njemačka, 2020. str. 1-6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1090598 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
UrTra2D – Urban Traffic 2D Object Detection
Dataset
Autori
Jelić, Borna ; Grbić, Ratko ; Vranješ, Mario ; Bjelica, Milan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of 10th IEEE International Conference of Consumer Technology
/ - , 2020, 1-6
Skup
10th IEEE International Conference of Consumer Technology
Mjesto i datum
Berlin, Njemačka, 09.11.2020. - 12.11.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Autonomous driving ; Object detection ; Dataset ; Urban traffic
Sažetak
With progress being made in the field of artificial intelligence and especially machine learning, tech and vehicle companies acquired a powerful tool and made a large step towards realisation of a fully autonomous vehicle. Along with the exploding development of more and more powerful hardware, deep learning has become one of the most dominant fields of research in the automotive domain, succeeding the classical computer vision methods. However, to be able to apply deep learning methods to solve a problem, large and appropriate datasets are required in developing a solution, as there is never enough data for deep learning. In this paper, Urban Traffic 2D Object Detection (UrTra2D) dataset is presented, which is intended for training 2D detectors of specific objects common for urban traffic scenes. The data was recorded with an affordable camera mounted inside the vehicle. The dataset contains video sequences and labelled frames of the traffic in the city of Osijek in different weather conditions during both day and night. There are 5 770 labelled frames, totalling in 22 764 labelled objects throughout 11 categories. The UrTra2D dataset is freely available to the research community upon request.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek