Dog Face Detection Using YOLO Network
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...
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Brno University of Technology
2020-12-01
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doaj-83f051dd25e0461696d08b2ed81101b02021-07-20T13:20:35ZengBrno University of TechnologyMendel1803-38142571-37012020-12-0126210.13164/mendel.2020.2.017Dog Face Detection Using YOLO NetworkAlzbeta Tureckova0Tomas Holik1Zuzana Kominkova Oplatkova2Tomas Bata University in Zlin, Faculty of Applied Informatics, Czech RepublicTomas Bata University in Zlin, Faculty of Applied Informatics, Czech RepublicTomas Bata University in Zlin, Faculty of Applied Informatics, Czech Republic 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. https://mendel-journal.org/index.php/mendel/article/view/121Deep LearningDeep Convolution NetworksObject detectionDog Face DetectionYOLOiOS Mobile Application |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alzbeta Tureckova Tomas Holik Zuzana Kominkova Oplatkova |
spellingShingle |
Alzbeta Tureckova Tomas Holik Zuzana Kominkova Oplatkova Dog Face Detection Using YOLO Network Mendel Deep Learning Deep Convolution Networks Object detection Dog Face Detection YOLO iOS Mobile Application |
author_facet |
Alzbeta Tureckova Tomas Holik Zuzana Kominkova Oplatkova |
author_sort |
Alzbeta Tureckova |
title |
Dog Face Detection Using YOLO Network |
title_short |
Dog Face Detection Using YOLO Network |
title_full |
Dog Face Detection Using YOLO Network |
title_fullStr |
Dog Face Detection Using YOLO Network |
title_full_unstemmed |
Dog Face Detection Using YOLO Network |
title_sort |
dog face detection using yolo network |
publisher |
Brno University of Technology |
series |
Mendel |
issn |
1803-3814 2571-3701 |
publishDate |
2020-12-01 |
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.
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topic |
Deep Learning Deep Convolution Networks Object detection Dog Face Detection YOLO iOS Mobile Application |
url |
https://mendel-journal.org/index.php/mendel/article/view/121 |
work_keys_str_mv |
AT alzbetatureckova dogfacedetectionusingyolonetwork AT tomasholik dogfacedetectionusingyolonetwork AT zuzanakominkovaoplatkova dogfacedetectionusingyolonetwork |
_version_ |
1721293750728130560 |