Analysis of dogs’ sleep patterns using convolutional neural networks

Zamansky, A, Sinitca, AM, Kaplun, DI, Plazner, M, Schork, IG, Young, RJ ORCID: and de Azevedo, CS 2019, Analysis of dogs’ sleep patterns using convolutional neural networks , in: 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany.

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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.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: Lecture Notes in Computer Science
Publisher: Springer
Series Name: Lecture Notes in Computer Science
ISBN: 9783030305086
ISSN: 0302-9743
Related URLs:
Depositing User: Professor Robert Young
Date Deposited: 31 Oct 2019 09:50
Last Modified: 16 Feb 2022 03:03

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