Correspondence edit distance to obtain a set of weighted means of graph correspondences.
- Submitting institution
-
Robert Gordon University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- Moreno-Garcia_1
- Type
- D - Journal article
- DOI
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10.1016/j.patrec.2018.08.027
- Title of journal
- Pattern Recognition Letters
- Article number
- -
- First page
- 29
- Volume
- 134
- Issue
- -
- ISSN
- 1872-7344
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- 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
-
-
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The novel method and repository presented in this paper (https://drive.google.com/open?id=1tA7Fs7NgMbVWdkK5Jq7smNxN90Ot7LdP) are widely used by the graph matching community to solve pattern recognition and machine vision problems. The collaboration with University of Munster (Germany) and University Rovira i Virgili (Spain) was supported by a Scottish Informatics and Computer Science Alliance (SICSA) visiting researcher grant (https://www.sicsa.ac.uk/research-exchanges-pece/), during which the team extended the correspondence method to the Oil & Gas engineering drawing digitisation problem (https://doi.org/10.1016/j.compind.2020.103198).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
