- Tytuł:
- Vehicle classification using the convolution neural network approach
- Autorzy:
-
Trivedi, Janak
Devi, Mandalapu Sarada
Dhara, Dave - Powiązania:
- https://bibliotekanauki.pl/articles/2091225.pdf
- Data publikacji:
- 2021
- Wydawca:
- Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
- Tematy:
-
convolution neural network
vehicle classification
deep learning
intelligent transportation system
konwolucyjna sieć neuronowa
klasyfikacja pojazdów
uczenie głębokie
inteligentny system transportowy - Opis:
- We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset’s different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic.
- Źródło:
-
Zeszyty Naukowe. Transport / Politechnika Śląska; 2021, 112; Bibliogr. 13 poz.
0209-3324
2450-1549 - Pojawia się w:
- Zeszyty Naukowe. Transport / Politechnika Śląska
- Dostawca treści:
- Biblioteka Nauki
Artykuł