| Stochastic Multi-object Guidance Laws for Interception and Rendezvous Problems | 0 | 0.34 | 2022 |
| A Formulation of the Adversarial Risk for Multiobject Filtering | 0 | 0.34 | 2021 |
| Joint Registration and Fusion of an Infrared Camera and Scanning Radar in a Maritime Context | 3 | 0.39 | 2020 |
| Fusion of Finite-Set Distributions: Pointwise Consistency and Global Cardinality. | 0 | 0.34 | 2019 |
| A Second-Order PHD Filter With Mean and Variance in Target Number. | 1 | 0.35 | 2018 |
| Multitarget Filtering With Linearized Complexity. | 2 | 0.38 | 2018 |
| Latent Parameter Estimation in Fusion Networks Using Separable Likelihoods. | 0 | 0.34 | 2018 |
| Fusion of finite set distributions: Pointwise consistency and global cardinality. | 2 | 0.36 | 2018 |
| The CPHD Filter With Target Spawning. | 4 | 0.43 | 2017 |
| A Tractable Forward- Backward CPHD Smoother. | 3 | 0.41 | 2017 |
| A Cooperative Approach to Sensor Localisation in Distributed Fusion Networks. | 3 | 0.39 | 2016 |
| Bayesian data assimilation based on a family of outer measures. | 0 | 0.34 | 2016 |
| Marker-Less Stage Drift Correction in Super-Resolution Microscopy Using the Single-Cluster PHD Filter. | 3 | 0.39 | 2016 |
| A sequential Monte Carlo approximation of the HISP filter | 0 | 0.34 | 2015 |
| Cooperative sensor localisation in distributed fusion networks by exploiting non-cooperative targets | 5 | 0.50 | 2014 |
| A novel approach to image calibration in super-resolution microscopy | 1 | 0.35 | 2014 |
| Accelerating the Single Cluster PHD Filter with a GPU implementation. | 2 | 0.39 | 2014 |
| Regional Variance for Multi-Object Filtering | 6 | 0.66 | 2014 |
| Faà Di Bruno's formula and volterra series | 1 | 0.37 | 2014 |
| A unified approach for multi-object triangulation, tracking and camera calibration. | 3 | 0.42 | 2014 |
| SLAM with SC-PHD Filters: An Underwater Vehicle Application. | 7 | 0.47 | 2014 |
| Bayesian estimation of multi-object systems with independently identically distributed correlations | 1 | 0.39 | 2014 |
| SLAM With Dynamic Targets via Single-Cluster PHD Filtering. | 24 | 1.15 | 2013 |
| The PHD filter for extended target tracking with estimable extent shape parameters of varying size. | 8 | 0.58 | 2012 |
| Disparity space: A parameterisation for Bayesian triangulation from multiple cameras. | 1 | 0.35 | 2012 |
| Slam With Single Cluster Phd Filters | 0 | 0.34 | 2012 |
| Incorporating track uncertainty into the OSPA metric. | 8 | 0.71 | 2011 |
| Information measures in distributed multitarget tracking | 11 | 1.04 | 2011 |
| A Note on the Reward Function for PHD Filters with Sensor Control | 49 | 2.49 | 2011 |
| Fast sequential Monte Carlo PHD smoothing | 2 | 0.38 | 2011 |
| The single-group PHD filter: An analytic solution | 17 | 1.03 | 2011 |
| Improved SMC implementation of the PHD filter. | 50 | 3.02 | 2010 |
| Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR | 26 | 1.67 | 2010 |
| Extended object filtering using spatial independent cluster processes. | 16 | 1.05 | 2010 |
| The Cramer-Rao Lower Bound for 3-D state estimation from rectified stereo cameras. | 2 | 0.42 | 2010 |
| First-moment multi-object forward-backward smoothing. | 2 | 0.48 | 2010 |
| Performance evaluation of multi-target tracking using the OSPA metric. | 13 | 1.20 | 2010 |
| Forward-backward sequential Monte Carlo smoothing for joint target detection and tracking | 4 | 0.70 | 2009 |
| PHD Filtering with target amplitude feature. | 3 | 0.61 | 2008 |
| Convergence Analysis of the Gaussian Mixture PHD Filter | 45 | 6.33 | 2007 |
| The Gm-Phd Filter Multiple Target Tracker | 32 | 4.51 | 2006 |
