A novel marine radar targets extraction approach based on sequential images and Bayesian Network
- Submitting institution
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Liverpool John Moores University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1194
- Type
- D - Journal article
- DOI
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10.1016/j.oceaneng.2016.04.030
- Title of journal
- Ocean Engineering
- Article number
- -
- First page
- 64
- Volume
- 120
- Issue
- -
- ISSN
- 0029-8018
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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B - LOOM
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work led to fully-funded keynote addresses at ICTIS2017 & 9th ICUTS (https://csce.ca/en/event/the-4th-international-conference-on-transportation-information-and-safety-ictis/), and the 2nd ICSRS conference, 2017. This research was partially funded by the Natural Science Foundation of China (NSFC grant numbers 61503289/2012-2015 (£100k) and 51479158/2014-2017 (£120k) and Innovation Groups Project of NSFC (2013CFA007/2013-2016, £200k). This research led to an EU-H2020 research grant (RESET, €1.42m, 2017-2021, coordinated by LJMU) and has been used by three industrial organisations including Shanghai Bestway Enterprise Development Group Co. to improve their safety security surveillance (L. Liu, Technical Manager, lliu@bestwaysh.com). This work has led to two patents granted (no.-201710723562.2 and no.-201710761707.8).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -