Mobile Stride Length Estimation with Deep Convolutional Neural Networks.

Hannink J, Kautz T, Pasluosta CF, Barth J, Schülein S, Gaßmann KG, Klucken J, Eskofier B (2018)

Publication Status: Published

Publication Type: Journal article

Publication year: 2018

Journal

IEEE Journal of Biomedical and Health Informatics Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 22

Pages Range: 354 - 362

Journal Issue: 2

URI: https://www.mad.tf.fau.de/files/2017/06/Hannink-et-al.-2017-Mobile-Stride-Length-Estimation-with-Deep-Convolutional-Neural-Networks-1.pdf

DOI: 10.1109/JBHI.2017.2679486

Authors with CRIS profile

Julius Hannink Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Thomas Kautz Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Cristian Federico Pasluosta Jens Barth Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Samuel Schülein Medizinische Fakultät Karl-Günter Gaßmann
Jochen Klucken Medizinische Fakultät Björn Eskofier Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics)

Additional Organisation(s)

Machine Learning and Data Analytics Lab

Involved external institutions

Malteser Waldkrankenhaus St. Marien

Germany (DE)

How to cite

APA:

Hannink, J., Kautz, T., Pasluosta, C.F., Barth, J., Schülein, S., Gaßmann, K.-G.,... Eskofier, B. (2018). Mobile Stride Length Estimation with Deep Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22(2), 354 - 362. https://doi.org/10.1109/JBHI.2017.2679486

MLA:

Hannink, Julius, et al. "Mobile Stride Length Estimation with Deep Convolutional Neural Networks." IEEE Journal of Biomedical and Health Informatics 22.2 (2018): 354 - 362.

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