Pregled bibliografske jedinice broj: 85085
LABAQM - A System for Qualitative Modelling and Analysis of Animal Behaviour
LABAQM - A System for Qualitative Modelling and Analysis of Animal Behaviour // Proceedings of the 13th International Conference on Information and Intelligent Systems, IIS 2002
Varaždin, 2002. str. 267-278 (predavanje, domaća recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 85085 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
LABAQM - A System for Qualitative Modelling and Analysis of Animal Behaviour
Autori
Matetić, Maja ; Ribarić, Slobodan ; Ipšić, Ivo
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 13th International Conference on Information and Intelligent Systems, IIS 2002
/ - Varaždin, 2002, 267-278
Skup
13th International Conference on Information and Intelligent Systems, IIS 2002
Mjesto i datum
Varaždin, Hrvatska, 25.09.2002. - 27.09.2002
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Domaća recenzija
Ključne riječi
dynamic vision system ; qualitative modelling ; conceptual clustering ; hidden Markov models of characteristic behaviours.
Sažetak
Tracking of a laboratory animal and its behaviour interpretation based on frame sequence analysis have been traditionally quantitative and typically generates large amounts of temporally evolving data. In our work we are dealing with higher-level approaches such as conceptual clustering and qualitative modelling in order to represent data obtained by tracking. We present the LABAQM system developed for the analysis of laboratory animal behaviours. It is based on qualitative modelling of animal motions. We are dealing with the cognitive phase of the laboratory animal behaviour analysis as a part of the pharmacological experiments. The system is based on the quantitative data from the tracking application and incomplete domain background knowledge. The LABAQM system operates in two main phases: behaviour learning and behaviour analysis. The behaviour learning and behaviour analysis phase are based on symbol sequences, obtained by the transformation of the quantitative data. Behaviour learning phase includes supervised learning procedure, unsupervised learning procedure and their combination. The fusion of supervised and unsupervised learning procedures produces more robust models of characteristic behaviours, which are used in the behaviour analysis phase.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
009033
Ustanove:
Filozofski fakultet, Rijeka,
Fakultet elektrotehnike i računarstva, Zagreb