Photo of Prof Simon Maskell

Prof Simon Maskell MEng, MA, PhD, FIET, CEng

Professor of Autonomous Systems Electrical Engineering and Electronics

    Publications

    2020

    A Fast Parallel Particle Filter for Shared Memory Systems (Journal article)

    Varsi, A., Taylor, J., Kekempanos, L., Pyzer Knapp, E., & Maskell, S. (2020). A Fast Parallel Particle Filter for Shared Memory Systems. IEEE Signal Processing Letters, 27, 1570-1574. doi:10.1109/LSP.2020.3014035

    DOI: 10.1109/LSP.2020.3014035

    A SMC Sampler for Joint Tracking and Destination Estimation from Noisy Data (Conference Paper)

    Vladimirov, L., & Maskell, S. (2020). A SMC Sampler for Joint Tracking and Destination Estimation from Noisy Data. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE. doi:10.23919/fusion45008.2020.9190463

    DOI: 10.23919/fusion45008.2020.9190463

    Bernoulli merging for the Poisson multi-Bernoulli mixture filter (Conference Paper)

    Fontana, M., Garcia-Fenandez, A. F., & Maskell, S. (2020). Bernoulli merging for the Poisson multi-Bernoulli mixture filter. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE. doi:10.23919/fusion45008.2020.9190443

    DOI: 10.23919/fusion45008.2020.9190443

    Continuous-discrete trajectory PHD and CPHD filters (Conference Paper)

    Garcia-Fernandez, A. F., & Maskell, S. (2020). Continuous-discrete trajectory PHD and CPHD filters. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE. doi:10.23919/fusion45008.2020.9190298

    DOI: 10.23919/fusion45008.2020.9190298

    Integrated Expected Likelihood Particle Filters (Conference Paper)

    Ransom, M. J., Vladimirov, L., Horridge, P. R., Ralph, J. F., & Maskell, S. (2020). Integrated Expected Likelihood Particle Filters. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE. doi:10.23919/fusion45008.2020.9190387

    DOI: 10.23919/fusion45008.2020.9190387

    Robust and Efficient Image Alignment Method Using the Student-t Distribution (Conference Paper)

    Zhou, Y., & Maskell, S. (2020). Robust and Efficient Image Alignment Method Using the Student-t Distribution. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE. doi:10.23919/fusion45008.2020.9190357

    DOI: 10.23919/fusion45008.2020.9190357

    Reliability Validation of Learning Enabled Vehicle Tracking (Journal article)

    Sun, Y., Zhou, Y., Maskell, S., Sharp, J., & Huang, X. (n.d.). Reliability Validation of Learning Enabled Vehicle Tracking. Retrieved from http://arxiv.org/abs/2002.02424v1

    Continuous-discrete multiple target filtering: PMBM, PHD and CPHD filter implementations (Journal article)

    Garcia-Fernandez, A., & Maskell, S. (2020). Continuous-discrete multiple target filtering: PMBM, PHD and CPHD filter implementations. Continuous-discrete multiple target filtering: PMBM, PHD and CPHD filter implementations. doi:10.1109/TSP.2020.2968247

    DOI: 10.1109/TSP.2020.2968247

    Weather effects on obstacle detection for autonomous car (Conference Paper)

    Song, R., Wetherall, J., Maskell, S., & Ralph, J. F. (2020). Weather effects on obstacle detection for autonomous car. In VEHITS 2020 - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems (pp. 331-341).

    2019

    Efficient Estimation of Probability of Conflict Between Air Traffic Using Subset Simulation (Journal article)

    Mishra, C., Maskell, S., Au, S. -K., & Ralph, J. F. (2019). Efficient Estimation of Probability of Conflict Between Air Traffic Using Subset Simulation. IEEE Transactions on Aerospace and Electronic Systems, 55(6), 2719-2742. doi:10.1109/TAES.2019.2899714

    DOI: 10.1109/TAES.2019.2899714

    Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR (Journal article)

    van Stekelenborg, J., Ellenius, J., Maskell, S., Bergvall, T., Caster, O., Dasgupta, N., . . . Pirmohamed, M. (2019). Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR. DRUG SAFETY, 42(12), 1393-1407. doi:10.1007/s40264-019-00858-7

    DOI: 10.1007/s40264-019-00858-7

    A Generic Anomaly Detection Approach Applied to Mixture-of-unigrams and Maritime Surveillance Data (Conference Paper)

    Zhou, Y., Wright, J., Maskell, S., & IEEE. (2019). A Generic Anomaly Detection Approach Applied to Mixture-of-unigrams and Maritime Surveillance Data. In 2019 SYMPOSIUM ON SENSOR DATA FUSION: TRENDS, SOLUTIONS, APPLICATIONS (SDF 2019). Retrieved from http://gateway.webofknowledge.com/

    On the Bridges: Insight Into the Current and Future Use of Automated Systems as Seen by Royal Navy Personnel (Journal article)

    Barrett-Pink, C., Alison, L., Maskell, S., & Shortland, N. (2019). On the Bridges: Insight Into the Current and Future Use of Automated Systems as Seen by Royal Navy Personnel. Journal of Cognitive Engineering and Decision Making, 13(3), 127-145. doi:10.1177/1555343419855850

    DOI: 10.1177/1555343419855850

    A Multi-Sensor Simulation Environment for Autonomous Cars (Conference Paper)

    Song, R., Horridge, P., Pemberton, S., Wetherall, J., Maskell, S., Ralph, J., & IEEE. (2019). A Multi-Sensor Simulation Environment for Autonomous Cars. In 2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019). Retrieved from http://gateway.webofknowledge.com/

    Detecting and Tracking Small Moving Objects in Wide Area Motion Imagery (WAMI) Using Convolutional Neural Networks (CNNs) (Conference Paper)

    Zhou, Y., Maskell, S., & IEEE. (2019). Detecting and Tracking Small Moving Objects in Wide Area Motion Imagery (WAMI) Using Convolutional Neural Networks (CNNs). In 2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019). Retrieved from http://gateway.webofknowledge.com/

    Recommendations on the Use of Mobile Applications for the Collection and Communication of Pharmaceutical Product Safety Information: Lessons from IMI WEB-RADR (Journal article)

    Pierce, C. E., de Vries, S. T., Bodin-Parssinen, S., Harmark, L., Tregunno, P., Lewis, D. J., . . . Mol, P. G. M. (2019). Recommendations on the Use of Mobile Applications for the Collection and Communication of Pharmaceutical Product Safety Information: Lessons from IMI WEB-RADR. DRUG SAFETY, 42(4), 477-489. doi:10.1007/s40264-019-00813-6

    DOI: 10.1007/s40264-019-00813-6

    A CPHD Approximation Based on a Discrete-Gamma Cardinality Model (Journal article)

    De Melo, F., & Maskell, S. (n.d.). A CPHD approximation based on a discrete-Gamma cardinality model. IEEE Transactions on Signal Processing.

    DOI: 10.1109/TSP.2018.2881659

    A Single SMC Sampler on MPI that Outperforms a Single MCMC Sampler (Journal article)

    Varsi, A., Kekempanos, L., Thiyagalingam, J., & Maskell, S. (n.d.). A Single SMC Sampler on MPI that Outperforms a Single MCMC Sampler. Retrieved from http://arxiv.org/abs/1905.10252v1

    2018

    Convolutional Neural Networks for Aerial Vehicle Detection and Recognition (Conference Paper)

    Soleimani, A., Nasrabadi, N. M., Griffith, E., Ralph, J., Maskell, S., & IEEE. (2018). Convolutional Neural Networks for Aerial Vehicle Detection and Recognition. In NAECON 2018 - IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (pp. 186-191). Retrieved from http://gateway.webofknowledge.com/

    Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project. (Journal article)

    Caster, O., Dietrich, J., Kuerzinger, M. -L., Lerch, M., Maskell, S., Noren, G. N., . . . van Stekelenborg, J. (2018). Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project. DRUG SAFETY, 41(12), 1355-1369. doi:10.1007/s40264-018-0699-2

    DOI: 10.1007/s40264-018-0699-2

    Comparing interrelationships between features and embedding methods for multiple-view fusion (Conference Paper)

    Piroddi, R., Goulermas, Y., Maskell, S., Ralph, J., & IEEE. (2018). Comparing interrelationships between features and embedding methods for multiple-view fusion. In 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 1503-1510). Retrieved from http://gateway.webofknowledge.com/

    Fusing Bearing-only Measurements With and Without Propagation Delays Using Particle Trajectories (Conference Paper)

    Horridge, P., Maskell, S., & IEEE. (2018). Fusing Bearing-only Measurements With and Without Propagation Delays Using Particle Trajectories. In 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 989-996). Retrieved from http://gateway.webofknowledge.com/

    Comparing Interrelationships Between Features and Embedding Methods for Multiple-View Fusion. (Conference Paper)

    Piroddi, R., Goulermas, J. Y., Maskell, S., & Ralph, J. F. (2018). Comparing Interrelationships Between Features and Embedding Methods for Multiple-View Fusion.. In FUSION (pp. 1-5). IEEE. Retrieved from http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8442112

    Dynamical model selection near the quantum-classical boundary (Journal article)

    Ralph, J. F., Toros, M., Maskell, S., Jacobs, K., Rashid, M., Setter, A. J., & Ulbricht, H. (2018). Dynamical model selection near the quantum-classical boundary. PHYSICAL REVIEW A, 98(1). doi:10.1103/PhysRevA.98.010102

    DOI: 10.1103/PhysRevA.98.010102

    Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach (Journal article)

    Bollegala, D., Maskell, S., Sloane, R., Hajne, J., & Pirmohamed, M. (2018). Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach. JMIR PUBLIC HEALTH AND SURVEILLANCE, 4(2), 292-303. doi:10.2196/publichealth.8214

    DOI: 10.2196/publichealth.8214

    Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach (Preprint) (Journal article)

    Bollegala, D., Maskell, S., Sloane, R., Hajne, J., & Pirmohamed, M. (n.d.). Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach (Preprint). doi:10.2196/preprints.8214

    DOI: 10.2196/preprints.8214

    A System for the Generation of Synthetic Wide Area Aerial Surveillance Imagery (Journal article)

    Griffith, E., Mishra, C., Ralph, J. F., & Maskell, S. (2018). A System for the Generation of Synthetic Wide Area Aerial Surveillance Imagery. Simulation Modelling Practice and Theory, 84, 286-308. doi:10.1016/j.simpat.2018.03.003

    DOI: 10.1016/j.simpat.2018.03.003

    Langevin Incremental Mixture Importance Sampling (Journal article)

    Fasiolo, M., de melo, F., & Maskell, S. (2018). Langevin Incremental Mixture Importance Sampling. Statistics and Computing, 28, 549-561. doi:10.1007/s11222-017-9747-5

    DOI: 10.1007/s11222-017-9747-5

    Uncertainty representation and evaluation for modelling and decision-making in information fusion (Journal article)

    De Villiers, J. P., Pavlin, G., Jousselme, A. L., Maskell, S., Waal, A. D. E., Laskey, K., . . . Costa, P. (2018). Uncertainty representation and evaluation for modelling and decision-making in information fusion. Journal of Advances in Information Fusion, 13(2), 198-215.

    2017

    Moving Object Detection Using Background Subtraction for a Moving Camera with Pronounced Parallax (Conference Paper)

    Zhou, Y., Maskell, S., & IEEE. (2017). Moving Object Detection Using Background Subtraction for a Moving Camera with Pronounced Parallax. In 2017 SENSOR DATA FUSION: TRENDS, SOLUTIONS, APPLICATIONS (SDF). Retrieved from http://gateway.webofknowledge.com/

    Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods (Journal article)

    Ralph, J. F., Maskell, S., & Kacobs, K. (2017). Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods. Physical Review A (Atomic, Molecular and Optical Physics), 96. doi:10.1103/PhysRevA.96.052306

    DOI: 10.1103/PhysRevA.96.052306

    MapReduce particle filtering with exact resampling and deterministic runtime (Journal article)

    Thiyagalingam, J., Kekempanos, L., & Maskell, S. (2017). MapReduce particle filtering with exact resampling and deterministic runtime. Eurasip Journal on Advances in Signal Processing, 2017, 23 pages. doi:10.1186/s13634-017-0505-9

    DOI: 10.1186/s13634-017-0505-9

    Beyond co-occurrence-based ADR detection from Social Media (Poster)

    Bollegala, D., Maskell, S., & Pirmohamed, M. (2017). Beyond co-occurrence-based ADR detection from Social Media. Poster session presented at the meeting of Unknown Conference. Retrieved from http://gateway.webofknowledge.com/

    Estimating the Pertinent Information Present in Social Media, not just what an Algorithm Detects (Poster)

    Maskell, S., Sloane, R., Perkins, S., Heap, J., Hajne, J., Jones, A., & Pirmohamed, M. (2017). Estimating the Pertinent Information Present in Social Media, not just what an Algorithm Detects. Poster session presented at the meeting of Unknown Conference. Retrieved from http://gateway.webofknowledge.com/

    Looking Longitudinally in Twitter: Reading More than 140 Characters (Poster)

    Maskell, S., Sloane, R., Hajne, J., Heap, J., Perkins, S., Griffith, E., . . . Pirmohamed, M. (2017). Looking Longitudinally in Twitter: Reading More than 140 Characters. Poster session presented at the meeting of Unknown Conference. Retrieved from http://gateway.webofknowledge.com/

    When does Social Media add Value to Pharmacovigilance? (Conference Paper)

    Maskell, S. (2017). When does Social Media add Value to Pharmacovigilance?. In DRUG SAFETY Vol. 40 (pp. 1040). Retrieved from http://gateway.webofknowledge.com/

    Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers (Journal article)

    Green, P. L., & Maskell, S. (2017). Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers. Mechanical Systems and Signal Processing, 93, 379-396. doi:10.1016/j.ymssp.2016.12.023

    DOI: 10.1016/j.ymssp.2016.12.023

    Nonlinear Kinematics for Improved Helicopter Tracking (Conference Paper)

    Clark, E. J., Griffith, E. J., Maskell, S., Ralph, J. F., & IEEE. (2017). Nonlinear Kinematics for Improved Helicopter Tracking. In 2017 20TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 1013-1018). Retrieved from http://gateway.webofknowledge.com/

    RB2— PF : A novel filter-based monocular visual odometry algorithm (Conference Paper)

    Zhou, Y., & Maskell, S. (2017). RB2— PF : A novel filter-based monocular visual odometry algorithm. In 2017 20th International Conference on Information Fusion (Fusion). IEEE. doi:10.23919/icif.2017.8009745

    DOI: 10.23919/icif.2017.8009745

    An intersection-centric auction-based traffic signal control framework (Chapter)

    Raphael, J., Sklar, E. I., & Maskell, S. (2017). An Intersection-Centric Auction-Based Traffic Signal Control Framework. In Understanding Complex Systems (pp. 121-142). Springer International Publishing. doi:10.1007/978-3-319-46331-5_6

    DOI: 10.1007/978-3-319-46331-5_6

    MapReduce Particle Filtering with Exact Resampling and Deterministic Runtime. (Artefact)

    Thiyagalingam, J., Kekempanos, L., & Maskell, S. (2017). MapReduce Particle Filtering with Exact Resampling and Deterministic Runtime. [Artefact].

    Parallelising Particle Filters with Deterministic Runtime on Distributed Memory Systems (Conference Paper)

    Varsi, A., Kekempanos, L., Thiyagalingam, J., & Maskell, S. (2017). Parallelising Particle Filters with Deterministic Runtime on Distributed Memory Systems. In IET 3rd International Conference on Intelligent Signal Processing (ISP 2017). Institution of Engineering and Technology. doi:10.1049/cp.2017.0357

    DOI: 10.1049/cp.2017.0357

    RB2 - PF: A Novel Filter-based Monocular Visual Odometry Algorithm (Conference Paper)

    Zhou, Y., Maskell, S., & IEEE. (2017). RB2 - PF: A Novel Filter-based Monocular Visual Odometry Algorithm. In 2017 20TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 897-904). Retrieved from http://gateway.webofknowledge.com/

    2016

    Accurate Admission Transcriptomic Signature of the Severity of Acute Pancreatitis (Other)

    Nunes, Q. M., Lane, B., Huang, W., Altaf, K., Rainbow, L., Armstrong, J., . . . Sutton, R. (2016). Accurate Admission Transcriptomic Signature of the Severity of Acute Pancreatitis. In PANCREAS (Vol. 45, Iss. 10, pp. 1530). Retrieved from http://gateway.webofknowledge.com/

    Geometric Separation of Superimposed Images (Conference Paper)

    Mehta, M. M., Griffith, E. J., Maskell, S., Ralph, J. F., & IEEE. (2016). Geometric Separation of Superimposed Images. In 2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 1244-1251). Retrieved from http://gateway.webofknowledge.com/

    Using a Bayesian Model for Confidence to Make Decisions that Consider Epistemic Regret (Conference Paper)

    Anderson, R., Hare, N., Maskell, S., & IEEE. (2016). Using a Bayesian Model for Confidence to Make Decisions that Consider Epistemic Regret. In 2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 264-269). Retrieved from http://gateway.webofknowledge.com/

    An empirical investigation of adaptive traffic control parameters (Conference Paper)

    Raphael, J., Sklar, E. I., & Maskell, S. (2016). An empirical investigation of adaptive traffic control parameters. In CEUR Workshop Proceedings Vol. 1678.

    Parameter estimation from big data using a sequential monte carlo sampler (Conference Paper)

    Green, P. L., & Maskell, S. (2016). Parameter estimation from big data using a sequential monte carlo sampler. In PROCEEDINGS OF ISMA2016 INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING AND USD2016 INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (pp. 4111-4119). Retrieved from http://gateway.webofknowledge.com/

    2015

    Social media and pharmacovigilance: A review of the opportunities and challenges (Journal article)

    Sloane, R., Osanlou, O., Lewis, D., Bollegala, D., Maskell, S., & Pirmohamed, M. (2015). Social media and pharmacovigilance: A review of the opportunities and challenges. BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 80(4), 910-920. doi:10.1111/bcp.12717

    DOI: 10.1111/bcp.12717

    Datasets reflecting students' and teachers' views on the use of learning technology in a UK university (Journal article)

    Limniou, M., Downes, J. J., & Maskell, S. (2015). Datasets reflecting students' and teachers' views on the use of learning technology in a UK university. BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY, 46(5), 1081-1091. doi:10.1111/bjet.12332

    DOI: 10.1111/bjet.12332

    First Steps Toward an Auction-Based Traffic Signal Controller (Conference Paper)

    Raphael, J., Maskell, S., & Sklar, E. (2015). First Steps Toward an Auction-Based Traffic Signal Controller. In ADVANCES IN PRACTICAL APPLICATIONS OF AGENTS, MULTI-AGENT SYSTEMS, AND SUSTAINABILITY Vol. 9086 (pp. 300-303). doi:10.1007/978-3-319-18944-4_32

    DOI: 10.1007/978-3-319-18944-4_32

    From Goods to Traffic: First Steps Toward an Auction-Based Traffic Signal Controller (Conference Paper)

    Raphael, J., Maskell, S., & Sklar, E. (2015). From Goods to Traffic: First Steps Toward an Auction-Based Traffic Signal Controller. In ADVANCES IN PRACTICAL APPLICATIONS OF AGENTS, MULTI-AGENT SYSTEMS, AND SUSTAINABILITY Vol. 9086 (pp. 187-198). doi:10.1007/978-3-319-18944-4_16

    DOI: 10.1007/978-3-319-18944-4_16

    2014

    Efficient Data Structures for Large Scale Tracking (Conference Paper)

    Lane, R. O., Briers, M., Cooper, T. M., Maskell, S. R., & IEEE. (2014). Efficient Data Structures for Large Scale Tracking. In 2014 17TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION). Retrieved from http://gateway.webofknowledge.com/

    Hybrid Gauss-Hermite Filter (Conference Paper)

    de Melo, F. E., & Maskell, S. (2014). Hybrid Gauss-Hermite Filter. In IET Conference on Data Fusion & Target Tracking 2014: Algorithms and Applications. Institution of Engineering and Technology. doi:10.1049/cp.2014.0530

    DOI: 10.1049/cp.2014.0530

    Probabilistic graphical detector fusion for localization of faces and facial parts (Conference Paper)

    Liu, C. Y., Zhou, Y., de Melo, F., & Maskell, S. (2014). Probabilistic graphical detector fusion for localization of faces and facial parts. In 2014 Sensor Data Fusion: Trends, Solutions, Applications (SDF). IEEE. doi:10.1109/sdf.2014.6954708

    DOI: 10.1109/sdf.2014.6954708

    2013

    Articulated human body parts detection based on cluster background subtraction and foreground matching (Journal article)

    Bhaskar, H., Mihaylova, L., & Maskell, S. (2013). Articulated human body parts detection based on cluster background subtraction and foreground matching. Neurocomputing, 100, 58-73. doi:10.1016/j.neucom.2011.12.039

    DOI: 10.1016/j.neucom.2011.12.039

    2011

    Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods (Journal article)

    Gning, A., Mihaylova, L., Maskell, S., Pang, S. K., & Godsill, S. (2011). Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods. IEEE Transactions on Signal Processing, 59(4), 1383-1396. doi:10.1109/tsp.2010.2103062

    DOI: 10.1109/tsp.2010.2103062

    2010

    Smoothing algorithms for state–space models (Journal article)

    Briers, M., Doucet, A., & Maskell, S. (2010). Smoothing algorithms for state–space models. Annals of the Institute of Statistical Mathematics, 62(1), 61-89. doi:10.1007/s10463-009-0236-2

    DOI: 10.1007/s10463-009-0236-2

    A Bayesian approach to joint tracking and identification of geometric shapes in video sequences (Journal article)

    Minvielle, P., Doucet, A., Marrs, A., & Maskell, S. (2010). A Bayesian approach to joint tracking and identification of geometric shapes in video sequences. Image and Vision Computing, 28(1), 111-123. doi:10.1016/j.imavis.2009.05.002

    DOI: 10.1016/j.imavis.2009.05.002

    2008

    A Bayesian approach to fusing uncertain, imprecise and conflicting information (Journal article)

    Maskell, S. (2008). A Bayesian approach to fusing uncertain, imprecise and conflicting information. Information Fusion, 9(2), 259-277. doi:10.1016/j.inffus.2007.02.003

    DOI: 10.1016/j.inffus.2007.02.003