Time-Series-Based Feature Selection and Clustering for Equine Activity Recognition Using Accelerometers-Reference-Cited by-同舟云学术

Time-Series-Based Feature Selection and Clustering for Equine Activity Recognition Using Accelerometers

Published:2023-06-01 Issue:11 Volume:23 Page:11855-11868
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

De Waele Timo¹^ORCID,Shahid Adnan¹^ORCID,Peralta Daniel¹^ORCID,Eerdekens Anniek²,Deruyck Margot²^ORCID,Tuyttens Frank A. M.³^ORCID,De Poorter Eli¹^ORCID

Affiliation:

1. IDLab Research Group, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium

2. Waves Research Group, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium

3. Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium

Funder

Fund for Scientific Research Flanders, FWO-Vlaanderen, Fonds Wetenschappelijk Onderzoek (FWO)-Strategisch Basisonderzoek (SB), Belgium

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10139852/10102796.pdf?arnumber=10102796

Reference30 articles.

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2. Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)

3. Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data

4. Automatic equine activity detection by convolutional neural networks using accelerometer data

5. The Balanced Accuracy and Its Posterior Distribution

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