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Tom SF Haines
Tom SF Haines
Computer Science, University of Bath
Verified email at bath.ac.uk - Homepage
Title
Cited by
Cited by
Year
Background Subtraction with Dirichlet Process Mixture Models
TSF Haines, T Xiang
Pattern Analysis and Machine Intelligence, IEEE Transactions on 36 (4), 670-683, 2014
2272014
Background subtraction with dirichlet processes
TSF Haines, T Xiang
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
842012
My Text in Your Handwriting
TSF Haines, OM Aodha, GJ Brostow
Transactions on Graphics, 2016
612016
Dirichlet process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations
W Del Pozzo, CPL Berry, A Ghosh, TSF Haines, LP Singer, A Vecchio
Monthly Notices of the Royal Astronomical Society 479 (1), 601-614, 2018
432018
Delta-dual hierarchical dirichlet processes: A pragmatic abnormal behaviour detector
TSF Haines, T Xiang
2011 International Conference on Computer Vision, 2198-2205, 2011
322011
Active rare class discovery and classification using dirichlet processes
TSF Haines, T Xiang
International Journal of Computer Vision 106, 315-331, 2014
242014
Integrating stereo with shape-from-shading derived orientation information
TF Haines, RC Wilson
British Machine Vision Conference (BMVC), 2007
202007
Texture stationarization: Turning photos into tileable textures
J Moritz, S James, TSF Haines, T Ritschel, T Weyrich
Computer graphics forum 36 (2), 177-188, 2017
182017
Active learning using dirichlet processes for rare class discovery and classification
TF Haines, T Xiang
British Machine Vision Conference, 2011
152011
Video topic modelling with behavioural segmentation
TSF Haines, T Xiang
Proceedings of the 1st ACM international workshop on Multimodal pervasive …, 2010
122010
Belief propagation with directional statistics for solving the shape-from-shading problem
TSF Haines, RC Wilson
Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008
122008
Combining shape-from-shading and stereo using Gaussian-Markov random fields
TSF Haines, RC Wilson
2008 19th International Conference on Pattern Recognition, 1-4, 2008
82008
Challenges of labelling unknown seabed munition dumpsites from acoustic and optical surveys: A case study at Skagerrak
O Bryan, RE Hansen, TSF Haines, N Warakagoda, A Hunter
Remote Sensing 14 (11), 2619, 2022
62022
Gaussian conjugate prior cheat sheet
TSF Haines
62011
Integrating Shape-from-Shading & Stereopsis
TSF Haines
University of York, 2009
52009
Synthetic cannabinoid receptor agonists are monoamine oxidase‐A selective inhibitors
SA Hindson, RC Andrews, MJ Danson, MW Van der Kamp, AE Manley, ...
The FEBS Journal 290 (12), 3243-3257, 2023
42023
Photochemical fingerprinting is a sensitive probe for the detection of synthetic cannabinoid receptor agonists; toward robust point-of-care detection
RC Andrews, B May, FJ Hernández, GE Cozier, PA Townsend, ...
Analytical Chemistry 95 (2), 703-713, 2023
42023
Instant detection of synthetic cannabinoids on physical matrices, implemented on a low-cost, ultraportable device
GE Cozier, RC Andrews, A Frinculescu, R Kumar, B May, T Tooth, ...
Analytical Chemistry 95 (37), 13829-13837, 2023
12023
Automatic recognition of underwater munitions from multi-view sonar surveys using semi supervised machine learning: a simulation study
O Bryan, TSF Haines, A Hunter, RE Hansen, N Warakagoda
Proceedings of Meetings on Acoustics 47 (1), 2022
12022
Swipe mosaics from video
M Reynolds, TSF Haines, GJ Brostow
arXiv preprint arXiv:1609.08080, 2016
12016
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