TY - JOUR
T1 - Automatic Animal Behavior Analysis
T2 - 14th International Symposium on Intelligent Systems, INTELS 2020
AU - Zamansky, Anna
AU - Sinitca, Aleksandr
AU - van der Linden, Dirk
AU - Kaplun, Dmitry
N1 - 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.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Animal Behaviour
KW - Artificial Intelligence
KW - Computational Analysis
KW - Computer Vision
KW - Machine Learning
KW - Spatio-temporal Data Processing
UR - http://www.scopus.com/inward/record.url?scp=85112725074&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2021.04.187
DO - 10.1016/j.procs.2021.04.187
M3 - Conference article
AN - SCOPUS:85112725074
VL - 186
SP - 661
EP - 668
JO - Procedia Computer Science
JF - Procedia Computer Science
SN - 1877-0509
Y2 - 14 December 2020 through 16 December 2020
ER -