Analysis of dogs’ sleep patterns using convolutional neural networks

Zamansky, A; Sinitca, AM; Kaplun, DI; Plazner, M; Schork, IG; Young, RJ; de Azevedo, CS

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.

Citation

Zamansky, A., Sinitca, A., Kaplun, D., Plazner, M., Schork, I., Young, R., & de Azevedo, C. Analysis of dogs’ sleep patterns using convolutional neural networks. Presented at 28th International Conference on Artificial Neural Networks, Munich, Germany

• Presentation Conference Type: Other
• Conference Name: 28th International Conference on Artificial Neural Networks
• Conference Location: Munich, Germany
• Publication Date: Sep 9, 2019
• Deposit Date: Oct 31, 2019
• Publicly Available Date: Sep 9, 2020
• Series Title: Lecture Notes in Computer Science
• Series Number: 11729
• Book Title: Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing
• ISBN: 9783030305086
• Publisher URL: https://doi.org/10.1007/978-3-030-30508-6_38
• Related Public URLs: https://link.springer.com/book/10.1007/978-3-030-30508-6#about
• Additional Information: Event Type : Conference