Dog face detection using yolo network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F20%3A63526298" target="_blank" >RIV/70883521:28140/20:63526298 - isvavai.cz</a>
Result on the web
<a href="https://mendel-journal.org/index.php/mendel/article/view/121" target="_blank" >https://mendel-journal.org/index.php/mendel/article/view/121</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.13164/mendel.2020.2.017" target="_blank" >10.13164/mendel.2020.2.017</a>
Alternative languages
Result language
angličtina
Original language name
Dog face detection using yolo network
Original language description
This work presents the real-world application of the object detection which belongs to one of the current research lines in computer vision. Researchers are commonly focused on human face detection. Compared to that, the current paper presents a challenging task of detecting a dog face instead that is an object with extensive variability in appearance. The system utilises YOLO network, a deep convolution neural network, to predict bounding boxes and class confidences simultaneously. This paper documents the extensive dataset of dog faces gathered from two different sources and the training procedure of the detector. The proposed system was designed for realization on mobile hardware. This Doggie Smile application helps to snapshot dogs at the moment when they face the camera. The proposed mobile application can simultaneously evaluate the gaze directions of three dogs in scene more than 13 times per second, measured on iPhone XR. The average precision of the dogface detection system is 0.92. © 2020, Brno University of Technology. All rights reserved.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Mendel
ISSN
1803-3814
e-ISSN
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Volume of the periodical
26
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
17-22
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85098254118