Thomas Ploetz
Cited by
Cited by
Deep, convolutional, and recurrent models for human activity recognition using wearables.
NY Hammerla, S Halloran, T Ploetz
Proc. IJCAI 2016 (arXiv preprint arXiv:1604.08880), 2016
Large scale population assessment of physical activity using wrist worn accelerometers: the UK biobank study
A Doherty, D Jackson, N Hammerla, T Plötz, P Olivier, MH Granat, T White, ...
PloS one 12 (2), e0169649, 2017
Ensembles of Deep LSTM Learners for Activity Recognition using Wearables
Y Guan, T Ploetz
PACM IMWUT 1 (2), 2017
Feature learning for activity recognition in ubiquitous computing
T Plötz, NY Hammerla, PL Olivier
Twenty-second international joint conference on artificial intelligence, 2011
Markov models for offline handwriting recognition: a survey
T Plötz, GA Fink
International Journal on Document Analysis and Recognition (IJDAR) 12, 269-298, 2009
The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices
M Kranz, A Möller, N Hammerla, S Diewald, P Olivier, L Roalter, T Plötz
Pervasive and Mobile Computing 9 (2), 203-215, 2013
Early detection of health and welfare compromises through automated detection of behavioural changes in pigs
SG Matthews, AL Miller, J Clapp, T Plötz, I Kyriazakis
The Veterinary Journal 217, 43-51, 2016
PD disease state assessment in naturalistic environments using deep learning
N Hammerla, T Ploetz, L Rochester, J Fisher, R Walker, PE Andras
Keele University, 2015
Optimising sampling rates for accelerometer-based human activity recognition
A Khan, N Hammerla, S Mellor, T Plötz
Pattern Recognition Letters 73, 33-40, 2016
Automated tracking to measure behavioural changes in pigs for health and welfare monitoring
SG Matthews, AL Miller, T PlÖtz, I Kyriazakis
Scientific reports 7 (1), 17582, 2017
Physical activity, sedentary behaviour and metabolic control following stroke: a cross-sectional and longitudinal study
SA Moore, K Hallsworth, T Plötz, GA Ford, L Rochester, MI Trenell
PloS one 8 (1), e55263, 2013
On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution
NY Hammerla, R Kirkham, P Andras, T Plötz
Proc. Int. Symposium on Wearable Computers (ISWC), 65-68, 2013
Multi-modal anchoring for human–robot interaction
J Fritsch, M Kleinehagenbrock, S Lang, T Plötz, GA Fink, G Sagerer
Robotics and Autonomous Systems 43 (2-3), 133-147, 2003
On Attention Models for Human Activity Recognition
VS Murahari, T Ploetz
Proc. Int. Symposium Wearable Computing (ISWC), 2018
Movement recognition technology as a method of assessing spontaneous general movements in high risk infants
C Marcroft, A Khan, N Embleton, M Trenell, T Ploetz
Frontiers in Neurology 5 (284), 2015
ClimbAX: Skill Assessment for Climbing Enthusiasts
C Ladha, N Hammerla, P Olivier, T Ploetz
Proc. Int. Conf. Ubiquitous Computing (UbiComp), 2013
Using Unlabeled Data in a Sparse-coding Framework for Human Activity Recognition
S Bhattacharya, P Nurmi, N Hammerla, T Ploetz
Pervasive and Mobile Computing, 2014
Dog's Life: Wearable Activity Recognition for Dogs
C Ladha, N Hammerla, E Hughs, P Olivier, T Ploetz
Proc. Int. Symp. Wearable Comp. (ISWC), 2013
Automatic assessment of problem behavior in individuals with developmental disabilities
T Plötz, NY Hammerla, A Rozga, A Reavis, N Call, GD Abowd
Proceedings of the 2012 ACM conference on ubiquitous computing, 391-400, 2012
Non-alcoholic fatty liver disease is associated with higher levels of objectively measured sedentary behaviour and lower levels of physical activity than matched healthy controls
K Hallsworth, C Thoma, S Moore, T Ploetz, QM Anstee, R Taylor, CP Day, ...
Frontline gastroenterology 6 (1), 44-51, 2015
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