Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks

Anna Zamansky; Aleksandr Sinitca; Dmitry Kaplun; Michael Plazner; Ivana Gabriela  Schork; Robert John Young

doi:10.1007/978-3-030-30508-6_38

Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks

Anna Zamansky, Aleksandr Sinitca, Dmitry Kaplun, Michael Plazner, Ivana Gabriela Schork, Robert John Young

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

19 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Lecture Notes in Computer Science
Subtitle of host publication	Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing.
Editors	I. Tekto, V. Kurkova, P. Karpov
Publisher	Springer Nature
Volume	11729
DOIs	https://doi.org/10.1007/978-3-030-30508-6_38
Publication status	Published - 9 Sept 2019
Externally published	Yes

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10.1007/978-3-030-30508-6_38

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Zamansky, A., Sinitca, A., Kaplun, D., Plazner, M., Schork, I. G., & Young, R. J. (2019). Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks. In I. Tekto, V. Kurkova, & P. Karpov (Eds.), Lecture Notes in Computer Science: Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. (Vol. 11729). Springer Nature. https://doi.org/10.1007/978-3-030-30508-6_38

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abstract = "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.",

author = "Anna Zamansky and Aleksandr Sinitca and Dmitry Kaplun and Michael Plazner and Schork, {Ivana Gabriela} and Young, {Robert John}",

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Zamansky, A, Sinitca, A, Kaplun, D, Plazner, M, Schork, IG & Young, RJ 2019, Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks. in I Tekto, V Kurkova & P Karpov (eds), Lecture Notes in Computer Science: Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. . vol. 11729, Springer Nature. https://doi.org/10.1007/978-3-030-30508-6_38

Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks. / Zamansky, Anna; Sinitca, Aleksandr; Kaplun, Dmitry et al.
Lecture Notes in Computer Science: Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. . ed. / I. Tekto; V. Kurkova; P. Karpov. Vol. 11729 Springer Nature, 2019.

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

TY - CHAP

T1 - Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks

AU - Zamansky, Anna

AU - Sinitca, Aleksandr

AU - Kaplun, Dmitry

AU - Plazner, Michael

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AU - Young, Robert John

PY - 2019/9/9

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AB - 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.

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M3 - Chapter (peer-reviewed)

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A2 - Tekto, I.

A2 - Kurkova, V.

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PB - Springer Nature

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Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks

Abstract

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