Search Results for author:
Found 9 papers, 0 papers with code
Variational Tracking and Redetection for Closely-spaced Objects in Heavy Clutter
The non-homogeneous Poisson process (NHPP) is a widely used measurement model that allows for an object to generate multiple measurements over time.
Consensus-based Distributed Variational Multi-object Tracker in Multi-Sensor Network
Then, we develop a distributed version leveraging the average consensus algorithm, which is theoretically equivalent to the centralised sensor fusion tracker and requires only local message passing with neighbouring sensors.
Driver Profiling and Bayesian Workload Estimation Using Naturalistic Peripheral Detection Study Data
Monitoring drivers' mental workload facilitates initiating and maintaining safe interactions with in-vehicle information systems, and thus delivers adaptive human machine interaction with reduced impact on the primary task of driving.
Non-Gaussian Process Regression
Standard GPs offer a flexible modelling tool for well-behaved processes.
Hidden Markov Models Applied To Intraday Momentum Trading With Side Information
To reflect this, learning is also carried out in the presence of side information.
Unsupervised Nonlinear Spectral Unmixing based on a Multilinear Mixing Model
In the community of remote sensing, nonlinear mixing models have recently received particular attention in hyperspectral image processing.
R-FUSE: Robust Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation
This paper proposes a robust fast multi-band image fusion method to merge a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image.
Multi-Band Image Fusion Based on Spectral Unmixing
The non-negativity and sum-to-one constraints resulting from the intrinsic physical properties of the abundances are introduced as prior information to regularize this ill-posed problem.
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation
A BCSKF can then be used to track the change in the DOA using the same framework.
