Analysis of dogs’ sleep patterns using convolutional neural networks

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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.

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Zamansky, A., Sinitca, A. M., Kaplun, D. I., Plazner, M., Schork, I. G., Young, R. J., & de Azevedo, C. S. (2019). Analysis of dogs’ sleep patterns using convolutional neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11729 LNCS, pp. 472–483). Springer Verlag. https://doi.org/10.1007/978-3-030-30508-6_38

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