Escolano, Francisco, Bonev, Boyan and Hancock, Edwin R. orcid.org/0000-0003-4496-2028 (2014) Quantum vs classical ranking in segment grouping. In: Structural, Syntactic, and Statistical Pattern Recognition:Joint IAPR International Workshop, S+SSPR 2014, Joensuu, Finland, August 20-22, 2014. Proceedings. Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014, 20-22 Aug 2014 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , GBR , pp. 203-212.
Abstract
In this paper we explore the use of ranking as a mean of guiding unsupervised image segmentation. Starting by the well known Pagerank algorithm we introduce an extension based on quantum walks. Pagerank (rank) can be used to prioritize the merging of segments embedded in uniform regions (parts of the image with roughly similar appearance statistics). Quantum Pagerank, on the other hand, gives high priority to boundary segments. This latter effect is due to the higher order interactions captured by quantum fluctuations. However we found that qrank does not always outperform its classical version. We analyze the Pascal VOC database and give Intersection over Union (IoU) performances.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Verlag 2014. This is an author produced version of a paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | quantum walks,random walks,ranking,segment grouping |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 15 Dec 2015 14:09 |
Last Modified: | 28 Jan 2025 00:02 |
Published Version: | https://doi.org/10.1007/978-3-662-44415-3_21 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-662-44415-3_21 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:85364 |
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