Result Details

Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications

ŠPAŇHEL, J.; SOCHOR, J.; MAKAROV, A. Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications. In 2018 14th Symposium on Neural Networks and Applications (NEUREL). Belgrade: IEEE Signal Processing Society, 2018. p. 1-5. ISBN: 978-1-5386-6974-7.
Type
conference paper
Language
English
Authors
Špaňhel Jakub, Ing., Ph.D., DCGM (FIT)
Sochor Jakub, Ing., Ph.D.
MAKAROV, A.
Abstract

We explore the implementation of vehicle
fine-grained type and color recognition based on neural
networks in a real-world application. We suggest changes to
the previously published method with respect to capabilities
of low-powered devices, such as Nvidia Jetson. Experimental
evaluation shows that the accuracy of MobileNet net slightly
decreases compared to ResNet-50 from 89.55% to 86.13%
while inference is 2.4× faster on Jetson.

Keywords

convolutional neural networks, similar vehicle type search, vehicle fine-grained recognition, vehicle reidentification  

Published
2018
Pages
1–5
Proceedings
2018 14th Symposium on Neural Networks and Applications (NEUREL)
Conference
2018 14th Symposium on Neural Networks and Applications (NEUREL)
ISBN
978-1-5386-6974-7
Publisher
IEEE Signal Processing Society
Place
Belgrade
DOI
10.1109/NEUREL.2018.8587012
UT WoS
000457745100031
EID Scopus
2-s2.0-85060947815
BibTeX 
@inproceedings{BUT155107,
  author="ŠPAŇHEL, J. and SOCHOR, J. and MAKAROV, A.",
  title="Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications",
  booktitle="2018 14th Symposium on Neural Networks and Applications (NEUREL)",
  year="2018",
  pages="1--5",
  publisher="IEEE Signal Processing Society",
  address="Belgrade",
  doi="10.1109/NEUREL.2018.8587012",
  isbn="978-1-5386-6974-7"
}
Projects
iARTIST - industry-Academia Research on Three-dimensional Image Sensing for Transportation, EU, Seventh Research Framework Programme, start: 2017-10-01, end: 2018-01-31, completed
Departments
Department of Computer Graphics and Multimedia (DCGM)
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