Ulf Jensen
Ulf Jensen
Researcher at the Pattern Recognition Lab, University of Erlangen
Verified email at - Homepage
Cited by
Cited by
Activity recognition in beach volleyball using a Deep Convolutional Neural Network: Leveraging the potential of Deep Learning in sports
T Kautz, BH Groh, J Hannink, U Jensen, H Strubberg, BM Eskofier
Data Mining and Knowledge Discovery 31, 1678-1705, 2017
Estimation of the knee flexion-extension angle during dynamic sport motions using body-worn inertial sensors
C Jakob, P Kugler, F Hebenstreit, S Reinfelder, U Jensen, D Schuldhaus, ...
Proceedings of the 8th International Conference on Body Area Networks, 289-295, 2013
Comparison of different algorithms for calculating velocity and stride length in running using inertial measurement units
M Zrenner, S Gradl, U Jensen, M Ullrich, BM Eskofier
Sensors 18 (12), 4194, 2018
Classification of kinematic swimming data with emphasis on resource consumption
U Jensen, F Prade, BM Eskofier
2013 IEEE International Conference on Body Sensor Networks, 1-5, 2013
Software-based performance and complexity analysis for the design of embedded classification systems
M Ring, U Jensen, P Kugler, B Eskofier
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
An IMU-based mobile system for golf putt analysis
U Jensen, M Schmidt, M Hennig, FA Dassler, T Jaitner, BM Eskofier
Sports Engineering 18, 123-133, 2015
Does the position of foot-mounted IMU sensors influence the accuracy of spatio-temporal parameters in endurance running?
M Zrenner, A Küderle, N Roth, U Jensen, B Dümler, BM Eskofier
Sensors 20 (19), 5705, 2020
Mobile recording system for sport applications
P Kugler, D Schuldhaus, U Jensen, B Eskofier
Proceedings of the 8th international symposium on computer science in sport …, 2011
Unobtrusive and energy-efficient swimming exercise tracking using on-node processing
U Jensen, P Blank, P Kugler, BM Eskofier
IEEE Sensors Journal 16 (10), 3972-3980, 2016
Approaching the accuracy–cost conflict in embedded classification system design
U Jensen, P Kugler, M Ring, BM Eskofier
Pattern Analysis and Applications 19, 839-855, 2016
Can machine learning techniques predict customer dissatisfaction? A feasibility study for the automotive industry.
S Meinzer, U Jensen, A Thamm, J Hornegger, BM Eskofier
Artif. Intell. Res. 6 (1), 80-90, 2017
Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors
D Schuldhaus, P Kugler, U Jensen, B Eskofier, H Schlarb, M Leible
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
Sensor-based instant golf putt feedback
U Jensen, P Kugler, F Dassler, B Eskofier
Proc. of the IACSS, 49-53, 2011
Generic features for biosignal classification
U Jensen, M Ring, B Eskofier
Sportinformatik 2012 112, 2012
Kinematic parameter evaluation for the purpose of a wearable running shoe recommendation
M Zrenner, M Ullrich, P Zobel, U Jensen, F Laser, BH Groh, B Duemler, ...
2018 IEEE 15th International Conference on Wearable and Implantable Body …, 2018
A wearable real-time activity tracker
U Jensen, H Leutheuser, S Hofmann, B Schuepferling, G Suttner, K Seiler, ...
Biomedical Engineering Letters 5, 147-157, 2015
Recording and analysis of biosignals on mobile devices
P Kugler¹, U Jensen¹, B Eskofier
Sportinformatik 2012, 182, 2012
Evaluation of foot kinematics during endurance running on different surfaces in real-world environments
M Zrenner, C Feldner, U Jensen, N Roth, R Richer, BM Eskofier
Proceedings of the 12th International Symposium on Computer Science in Sport …, 2020
Classification of kinematic golf putt data with emphasis on feature selection
U Jensen, B Eskofier, F Dassler
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
Design Considerations and Application Examples for Embedded Classification Systems
U Jensen
Dissertation, Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg …, 2016
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