Simon Maskell
Simon Maskell
Bestätigte E-Mail-Adresse bei liverpool.ac.uk - Startseite
TitelZitiert vonJahr
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
124272002
Smoothing algorithms for state–space models
M Briers, A Doucet, S Maskell
Annals of the Institute of Statistical Mathematics 62 (1), 61, 2010
2792010
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
2312005
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
2102001
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
1712006
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
1592005
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
A rao-blackwellised unscented Kalman filter
M Briers, SR Maskell, R Wright
Proceedings of the 6th International Conference of Information Fusion 1, 55-61, 2003
642003
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
592015
A Bayesian approach to fusing uncertain, imprecise and conflicting information
S Maskell
Information Fusion 9 (2), 259-277, 2008
592008
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
452002
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
332006
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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