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ŠPAŇHEL, J. SOCHOR, J. MAKAROV, A.
Original Title
Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications
Type
conference paper
Language
English
Original 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
Authors
ŠPAŇHEL, J.; SOCHOR, J.; MAKAROV, A.
Released
29. 10. 2018
Publisher
IEEE Signal Processing Society
Location
Belgrade
ISBN
978-1-5386-6974-7
Book
2018 14th Symposium on Neural Networks and Applications (NEUREL)
Pages from
1
Pages to
5
Pages count
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" }