A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos
- Submitting institution
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University of Strathclyde
- Unit of assessment
- 12 - Engineering
- Output identifier
- 87223081
- Type
- D - Journal article
- DOI
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10.1016/j.neucom.2018.01.076
- Title of journal
- Neurocomputing
- Article number
- -
- First page
- 68
- Volume
- 287
- Issue
- -
- ISSN
- 0925-2312
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- 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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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research was key to securing £29.5k Scottish Funding Council funding (https://pureportal.strath.ac.uk/en/projects/feasibility-study-for-remanufacturing-with-eagleisystems), £21.5k Science and Technology Facilities Council funding (https://pureportal.strath.ac.uk/en/projects/vip-stb-farm), and an EngD project with Canon Medical Research Europe (https://pureportal.strath.ac.uk/en/projects/multitask-deep-learning-from-images-for-clinical-decision-support).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -