Zamansky, Anna, Sinitca, Aleksandr, van der Linden, Dirk and Kaplun, Dmitry (2021) Automatic Animal Behavior Analysis: Opportunities for Combining Knowledge Representation with Machine Learning. Procedia Computer Science, 186. pp. 661-668. ISSN 1877-0509
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Abstract
Computational animal behavior analysis (CABA) is an emerging field which aims to apply AI techniques to support animal behavior analysis. The need for computational approaches which facilitate ‘objectivization’ and quantification of behavioral characteristics of animals is widely acknowledged within several animal-related scientific disciplines. State-of-the-art CABA approaches mainly apply machine learning (ML) techniques, combining it with approaches from computer vision and IoT. In this paper we highlight the potential applications of integrating knowledge representation approaches in the context of ML-based CABA systems, demonstrating the ideas using insights from an ongoing CABA project.
| Item Type: | Article |
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| Additional Information: | Funding information: This research was supported by a grant from the Ministry of Science and Technology of Israel and by RFBR according to the research project N 19-57-06007. |
| Subjects: | G400 Computer Science G500 Information Systems |
| Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
| Depositing User: | Elena Carlaw |
| Date Deposited: | 02 Dec 2021 15:58 |
| Last Modified: | 02 Dec 2021 16:00 |
| URI: | http://nrl.northumbria.ac.uk/id/eprint/47889 |
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