Facing Face Recognition with ResNet: Round One
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932934" target="_blank" >RIV/49777513:23520/17:43932934 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-66471-2_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-66471-2_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-66471-2_8" target="_blank" >10.1007/978-3-319-66471-2_8</a>
Alternative languages
Result language
angličtina
Original language name
Facing Face Recognition with ResNet: Round One
Original language description
This paper presents initial experiments of an application of deep residual network to face recognition task. We utilize 50-layer deep neural network ResNet architecture, which was presented last year on CVPR2016. The neural network was modified and then fine-tuned for face recognition purposes. The method was trained and tested on challenging Casia-WebFace database and the results were benchmarked with a simple convolutional neural network. Our experiments of classification of closed and open subset show the great potential of residual learning for face recognition.
Czech name
—
Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Interactive Collaborative Robotics Second International Conference, ICR 2017, Hatfield, UK, September 12-16, 2017, Proceedings
ISBN
978-3-319-66470-5
ISSN
0302-9743
e-ISSN
—
Number of pages
8
Pages from-to
67-74
Publisher name
Springer
Place of publication
Cham
Event location
Hatfield, United Kingdom
Event date
Sep 12, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000463337300008