Simon Maskell
Simon Maskell
Verified email at liverpool.ac.uk - Homepage
TitleCited byYear
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
MS Arulampalam, S Maskell, N Gordon, T Clapp
IEEE Transactions on signal processing 50 (2), 174-188, 2002
125532002
Smoothing algorithms for state–space models
M Briers, A Doucet, S Maskell
Annals of the Institute of Statistical Mathematics 62 (1), 61, 2010
2862010
Poisson models for extended target and group tracking
K Gilholm, S Godsill, S Maskell, D Salmond
Signal and Data Processing of Small Targets 2005 5913, 59130R, 2005
2322005
A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking
S Maskell, N Gordon
Target tracking: algorithms and applications (Ref. No. 2001/174), IEE 2, 21-215, 2001
2132001
Fast particle smoothing: If I had a million particles
M Klaas, M Briers, N De Freitas, A Doucet, S Maskell, D Lang
Proceedings of the 23rd international conference on Machine learning, 481-488, 2006
1752006
Recursive track-before-detect with target amplitude fluctuations
MG Rutten, NJ Gordon, S Maskell
IEE Proceedings-Radar, Sonar and Navigation 152 (5), 345-352, 2005
1602005
Comparison of EKF, pseudomeasurement, and particle filters for a bearing-only target tracking problem
X Lin, T Kirubarajan, Y Bar-Shalom, S Maskell
Signal and Data Processing of Small Targets 2002 4728, 240-250, 2002
1432002
Efficient particle filters for joint tracking and classification
NJ Gordon, S Maskell, T Kirubarajan
Signal and Data Processing of Small Targets 2002 4728, 439-449, 2002
1102002
Cramér-Rao bounds for non-linear filtering with measurement origin uncertainty
ML Hernandez, AD Marrs, NJ Gordon, SR Maskell, CM Reed
Proceedings of the Fifth International Conference on Information Fusion …, 2002
662002
Social media and pharmacovigilance: a review of the opportunities and challenges
R Sloane, O Osanlou, D Lewis, D Bollegala, S Maskell, M Pirmohamed
British journal of clinical pharmacology 80 (4), 910-920, 2015
642015
A rao-blackwellised unscented Kalman filter
M Briers, SR Maskell, R Wright
Sixth International Conference of Information Fusion, 2003. Proceedings of …, 2003
642003
A Bayesian approach to fusing uncertain, imprecise and conflicting information
S Maskell
Information Fusion 9 (2), 259-277, 2008
602008
Group object structure and state estimation with evolving networks and Monte Carlo methods
A Gning, L Mihaylova, S Maskell, SK Pang, S Godsill
IEEE Transactions on Signal Processing 59 (4), 1383-1396, 2010
502010
Efficient particle-based track-before-detect in Rayleigh noise
MG Rutten, NJ Gordon, S Maskell
International Conference on Information Fusion, 693-700, 2004
472004
Special issue on Monte Carlo methods for statistical signal processing
MS Arulampalam, S Maskell, N Gordon, T Clapp
IEEE Trans Signal Process 50 (2), 173, 2002
462002
Particle-based track-before-detect in Rayleigh noise
MG Rutten, NJ Gordon, S Maskell
Signal and Data Processing of Small Targets 2004 5428, 509-519, 2004
442004
Joint tracking of manoeuvring targets and classification of their manoeuvrability
S Maskell
EURASIP Journal on Advances in Signal Processing 2004 (15), 613289, 2004
402004
A unifying framework for multi-target tracking and existence
J Vermaak, S Maskell, M Briers
2005 7th International Conference on Information Fusion 1, 9 pp., 2005
352005
Real-time tracking of hundreds of targets with efficient exact JPDAF implementation
P Horridge, S Maskell
2006 9th International Conference on Information Fusion, 1-8, 2006
342006
Efficient particle filtering for multiple target tracking with application to tracking in structured images
S Maskell, MP Rollason, NJ Gordon, DJ Salmond
Signal and Data Processing of Small Targets 2002 4728, 251-262, 2002
332002
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