Jiaming Liang

Orcid: 0000-0002-1318-4481

Affiliations:
  • University of Cambridge, Department of Engineering, Signal Processing and Communication Laboratory, Cambridge, UK (PhD 2020)


According to our database1, Jiaming Liang authored at least 11 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Driver Profiling and Bayesian Workload Estimation Using Naturalistic Peripheral Detection Study Data.
IEEE Trans. Intell. Veh., January, 2024

2023
An Adaptive and Scalable Multi-Object Tracker Based on the Non-Homogeneous Poisson Process.
IEEE Trans. Signal Process., 2023

2022
Scalable Data Association and Multi-Target Tracking Under a Poisson Mixture Measurement Process.
Proceedings of the IEEE International Conference on Acoustics, 2022

2020
Simultaneous Intent Prediction and State Estimation Using an Intent-Driven Intrinsic Coordinate Model.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Inferring Dynamic Group Leadership Using Sequential Bayesian Methods.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Bayesian approaches to tracking, sensor fusion and intent prediction
PhD thesis, 2019

Driver and Passenger Identification From Smartphone Data.
IEEE Trans. Intell. Transp. Syst., 2019

On Destination Prediction Based on Markov Bridging Distributions.
IEEE Signal Process. Lett., 2019

Bayesian Intent Prediction for Fast Maneuvering Objects using Variable Rate Particle Filters.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Bayesian Fusion of Asynchronous Inertial, Speed and Position Data for Object Tracking.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
A Particle Filter Localisation System for Indoor Track Cycling Using an Intrinsic Coordinate Model.
Proceedings of the 21st International Conference on Information Fusion, 2018


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