A Generic Framework for Constraint-Driven Data Selection in Mobile Crowd Photographing
- Submitting institution
-
De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11037
- Type
- D - Journal article
- DOI
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10.1109/jiot.2017.2648860
- Title of journal
- IEEE Internet of Things Journal
- Article number
- -
- First page
- 284
- Volume
- 4
- Issue
- -
- ISSN
- 2327-4662
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- 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
-
4
- Research group(s)
-
-
- Citation count
- 29
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research represents the latest development in crowdsourcing sensing and collective wisdom, in particular, the PTree model is useful to select a subset with high utility coverage and low redundancy ratio from the high-throughout streaming data.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -