Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Nils Y. Hammerla"'
Publikováno v:
ACL
Word embedding-based similarity measures are currently among the top-performing methods on unsupervised semantic textual similarity (STS) tasks. Recent work has increasingly adopted a statistical view on these embeddings, with some of the top approac
Publikováno v:
EMNLP/IJCNLP (1)
Similarity measures based purely on word embeddings are comfortably competing with much more sophisticated deep learning and expert-engineered systems on unsupervised semantic textual similarity (STS) tasks. In contrast to commonly used geometric app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8196c927878a7a044de32e679a635fd8
http://arxiv.org/abs/1910.02902
http://arxiv.org/abs/1910.02902
Publikováno v:
Parkinsonism & Related Disorders. 33:44-50
Introduction\ud Current PD assessment methods have inherent limitations. There is need for an objective method to assist clinical decisions and to facilitate evaluation of treatments. Accelerometers, and analysis using artificial neural networks (ANN
Publikováno v:
ACL (1)
In this work we approach the task of learning multilingual word representations in an offline manner by fitting a generative latent variable model to a multilingual dictionary. We model equivalent words in different languages as different views of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b66673a1db51361a0e360490ea31f08a
http://arxiv.org/abs/1905.05547
http://arxiv.org/abs/1905.05547
Publikováno v:
NAACL-HLT (1)
A large body of research into semantic textual similarity has focused on constructing state-of-the-art embeddings using sophisticated modelling, careful choice of learning signals and many clever tricks. By contrast, little attention has been devoted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8dcb1f7264476e83aeff8c6f23ae2dd6
Publikováno v:
Pattern Recognition Letters. 73:33-40
Activity recognition with wearable sensing typically uses non-optimal sampling rates.Sampling rates are up to 57% higher than necessary leading to waste of resources.We develop a method for automated, task specific optimisation of sampling rates.Usin
Autor:
Aftab Khan, Eugen Berlin, Robin Thompson, Sebastian Mellor, Thomas Plötz, Roisin McNaney, Nils Y. Hammerla, Patrick Olivier
Publikováno v:
University of Bristol-PURE
Human activity recognition (HAR), i.e., the automated detection and classification of specific activities that a person pursues, is one of the core concerns of mobile and ubiquitous computing. Multimodal sensing facilities of modern mobile devices al
Autor:
Nicholas J. Wareham, Aiden R. Doherty, Rob Gillions, Malcolm H. Granat, Dan Jackson, Tim Peakman, Stephen J. Preece, Christoper G. Owen, Michael I. Trenell, Vincent T. van Hees, Nils Y. Hammerla, Thomas E. White, Patrick Olivier, Thomas Plötz, Soren Brage, S.M. Sheard
Publikováno v:
PLoS ONE
PLoS ONE, Vol 12, Iss 2, p e0169649 (2017)
PLoS ONE, Vol 12, Iss 2, p e0169649 (2017)
Background Physical activity has not been objectively measured in prospective cohorts with sufficiently large numbers to reliably detect associations with multiple health outcomes. Technological advances now make this possible. We describe the method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56c517237c2d01b9a2f9a913915c8741
https://openaccess.sgul.ac.uk/id/eprint/108480/7/journal.pone.0169649.pdf
https://openaccess.sgul.ac.uk/id/eprint/108480/7/journal.pone.0169649.pdf
Autor:
Patrick Olivier, Thomas Plötz, Matthias Kranz, Andreas Möller, Luis Roalter, Nils Y. Hammerla, Stefan Diewald
Publikováno v:
Pervasive and Mobile Computing. 9:203-215
We report on our extended research on GymSkill, a smartphone system for comprehensive physical exercising support, from sensor data logging, activity recognition to on-top skill assessment, using the phone’s built-in sensors. In two iterations, we
Autor:
Tom Nappey, Gavin Wood, Ahmed Kharrufa, Jonathan Hook, Hendrik Haeuser, Gerard Wilkinson, Patrick Olivier, Bradley Pursglove, Steve Hodges, Nils Y. Hammerla
Publikováno v:
CHI Extended Abstracts
We present an interactivity demonstration of Expressy. A system that augments existing touchscreen devices with a variety of continuous expressive interaction capabilities, using movement data from a wrist-worn IMU. Our demonstration comprises a set