Joint detection and tracking for stealth targets in noisy imagery based on variational Bayesian-sequential Monte Carlo-cardinality-balanced multitarget multi-Bernoulli filter-Reference-Cited by-同舟云学术

Joint detection and tracking for stealth targets in noisy imagery based on variational Bayesian-sequential Monte Carlo-cardinality-balanced multitarget multi-Bernoulli filter

Published:2020-02-27 Issue:01 Volume:29 Page:1
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:
Short-container-title:J. Electron. Imag.

Author:

Salim Ibrahim M.¹,Barbary Mohamed²,ElAzeem Mohamed H. Abd¹

Affiliation:

1. Arab Academy for Science Technology and Maritime Transport, Department of Electronics and Communicat

2. Alexandria University, Department of Electrical Engineering, Alexandria

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Reference22 articles.

1. Computationally Efficient Multi-Agent Multi-Object Tracking With Labeled Random Finite Sets

2. Multi‐model particle cardinality‐balanced multi‐target multi‐Bernoulli algorithm for multiple manoeuvring target tracking

3. Multiple Model Multi-Bernoulli Filters for Manoeuvering Targets

4. Joint Detection and Estimation of Multiple Objects From Image Observations

5. An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter

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