Analysis of Dogs' Sleep Patterns Using Convolutional Neural Networks

被引：16
|
作者：
Zamansky, Anna [1 ]
Sinitca, Aleksandr M. [2 ]
Kaplun, Dmitry, I [2 ]
Plazner, Michael [1 ]
Schork, Ivana G. [3 ]
Young, Robert J. [3 ]
de Azevedo, Cristiano S. [4 ]
机构：
[1] Univ Haifa, Informat Syst Dept, Haifa, Israel
[2] St Petersburg Electrotech Univ LETI, St Petersburg, Russia
[3] Univ Salford, Sch Environm & Life Sci, Manchester, England
[4] Univ Fed Ouro Preto, Dept Biodivers Evolut & Environm, Ouro Preto, Brazil
来源：
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2019: IMAGE PROCESSING, PT III | 2019年 / 11729卷
关键词：
Convolutional neural networks; Animal science; Animal welfare; Computer vision; VIDEO TRACKING; BEHAVIOR; SYSTEM;
D O I：
10.1007/978-3-030-30508-6_38
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Video-based analysis is one of the most important tools of animal behavior and animal welfare scientists. While automatic analysis systems exist for many species, this problem has not yet been adequately addressed for one of the most studied species in animal science-dogs. In this paper we describe a system developed for analyzing sleeping patterns of kenneled dogs, which may serve as indicator of their welfare. The system combines convolutional neural networks with classical data processing methods, and works with very low quality video from cameras installed in dogs shelters.
引用
收藏
页码：472 / 483
页数：12
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