Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Rashid Bakirov"'
Publikováno v:
Sports Medicine - Open, Vol 10, Iss 1, Pp 1-3 (2024)
Externí odkaz:
https://doaj.org/article/0b4ac2d8c4a5454183a8a5efdb9d147a
Autor:
Matteo Belvedere, Matthew R. Bennett, Daniel Marty, Marcin Budka, Sally C. Reynolds, Rashid Bakirov
Publikováno v:
PeerJ, Vol 6, p e4247 (2018)
Vertebrate tracks are subject to a wide distribution of morphological types. A single trackmaker may be associated with a range of tracks reflecting individual pedal anatomy and behavioural kinematics mediated through substrate properties which may v
Externí odkaz:
https://doaj.org/article/0666df60a0a24f4b98cc31c3a2d3540c
Autor:
Thilo Reich, Rashid Bakirov, Dominika Budka, Derek Kelly, James Smith, Tristan Richardson, Marcin Budka
Publikováno v:
Endocrine Abstracts.
Publikováno v:
Proceedings of the 4th ACM International workshop on Structuring and Understanding of Multimedia heritAge Contents.
Automation of machine learning model development is increasingly becoming an established research area. While automated model selection and automated data pre-processing have been studied in depth, there is, however, a gap concerning automated model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e49f5e84fb67f91c32061bb41ddf3069
http://arxiv.org/abs/1812.10793
http://arxiv.org/abs/1812.10793
Autor:
Daniel Marty, Matteo Belvedere, Matthew R. Bennett, Marcin Budka, Sally C. Reynolds, Rashid Bakirov
Publikováno v:
PeerJ
PeerJ, Vol 6, p e4247 (2018)
PeerJ, Vol 6, p e4247 (2018)
Vertebrate tracks are subject to a wide distribution of morphological types. A single trackmaker may be associated with a range of tracks reflecting individual pedal anatomy and behavioural kinematics mediated through substrate properties which may v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f29fbd57abe7c2a048dff445be53f208
https://eprints.bournemouth.ac.uk/30285/3/peerj-4247.pdf
https://eprints.bournemouth.ac.uk/30285/3/peerj-4247.pdf
Recent data-driven soft sensors often use multiple adaptive mechanisms to cope with non-stationary environments. These mechanisms are usually deployed in a prescribed order which does not change. In this work we use real world data from the process i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58d187f3a5bf16f13d35acc39359c75c
https://hdl.handle.net/10453/159486
https://hdl.handle.net/10453/159486
Publikováno v:
IJCNN
Existing adaptive predictive methods often use multiple adaptive mechanisms as part of their coping strategy in non-stationary environments. These mechanisms are usually deployed in a prescribed order which does not change. In this work we investigat