Academic Bibliography

Search 200 years of publications by Ghent University researchers.

Stef Vandermeeren

ORCID iD: 0000-0001-5073-0026

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Deep-learning-based step detection and step length estimation with a handheld IMU

Stef Vandermeeren and Heidi Steendam (UGent)

(2022) IEEE SENSORS JOURNAL. 22(24). p.24205-24221
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- PhD Thesis
- open access
Machine and deep learning and sensor fusion for pedestrian dead reckoning applications

Stef Vandermeeren

(2022)
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PDR/UWB based positioning of a shopping cart

Stef Vandermeeren and Heidi Steendam (UGent)

(2021) IEEE SENSORS JOURNAL. 21(9). p.10864-10878
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- Journal Article
- A1
- open access
Feature selection for machine learning based step length estimation algorithms

Stef Vandermeeren, Herwig Bruneel (UGent) and Heidi Steendam (UGent)

(2020) SENSORS. 20(3).
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- Conference Paper
- C3
- open access
Step detection using LSTM networks

Stef Vandermeeren, Herwig Bruneel (UGent) and Heidi Steendam (UGent)

(2019) 26th Symposium on Communications and Vehicular Technology in the Benelux (SCVT 2019), Abstracts.
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Feature selection for machine learning based step length estimation algorithms

Stef Vandermeeren, Herwig Bruneel (UGent) and Heidi Steendam (UGent)

(2018) Communications and Vehicular Technology (SCVT), 2018 IEEE Symposium.
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A feature ranking and selection algorithm for machine learning-based step counters

Stef Vandermeeren, Samuel Van de Velde, Herwig Bruneel (UGent) and Heidi Steendam (UGent)

(2018) IEEE SENSORS JOURNAL. 18(8). p.3255-3265
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- Journal Article
- A1
- open access
Experimental evaluation of UWB indoor positioning for sport postures

Matteo Ridolfi, Stef Vandermeeren, Jense Defraye, Heidi Steendam (UGent) , Joeri Gerlo (UGent) , Dirk De Clercq (UGent) , Jeroen Hoebeke (UGent) and Eli De Poorter (UGent)

(2018) SENSORS. 18(1).