- -

Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking

Show full item record

Pons Tomás, P.; Jaén Martínez, FJ.; Catalá Bolós, A. (2017). Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking. Expert Systems with Applications. 86:235-246. doi:10.1016/j.eswa.2017.05.063

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/102344

Files in this item

Item Metadata

Title: Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Embargo end date: 2019-11-15
Abstract:
[EN] There is growing interest in the automatic detection of animals' behaviors and body postures within the field of Animal Computer Interaction, and the benefits this could bring to animal welfare, enabling remote ...[+]
Subjects: Tracking system , Animal Computer Interaction , Depth-based tracking , Classification algorithms , Intelligent system
Copyrigths: Embargado
Source:
Expert Systems with Applications. (issn: 0957-4174 )
DOI: 10.1016/j.eswa.2017.05.063
Publisher:
Elsevier
Publisher version: http://doi.org/10.1016/j.eswa.2017.05.063
Thanks:
This work is funded by the European Development Regional Fund (EDRF-FEDER) and supported by Spanish MINECO with Project TIN2014-60077-R. It also received support from a postdoctoral fellowship within the VALi+d Program of ...[+]
Type: Artículo

This item appears in the following Collection(s)

Show full item record