Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU130799" target="_blank" >RIV/00216305:26230/18:PU130799 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/NEUREL.2018.8587012" target="_blank" >http://dx.doi.org/10.1109/NEUREL.2018.8587012</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NEUREL.2018.8587012" target="_blank" >10.1109/NEUREL.2018.8587012</a>
Alternative languages
Result language
angličtina
Original language name
Vehicle Fine-grained Recognition Based on Convolutional Neural Networks for Real-world Applications
Original language description
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 2.4x faster on Jetson.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 14th Symposium on Neural Networks and Applications (NEUREL)
ISBN
978-1-5386-6974-7
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
IEEE Signal Processing Society
Place of publication
Belgrade
Event location
SAVA Center Milentija Popovića 9 11070, Belgrade
Event date
Nov 20, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000457745100031