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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

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • 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

  • 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

  • EID of the result in the Scopus database

    2-s2.0-85098254118