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Signature features with the visibility transformation

Abstract:
In this paper we put the visibility transformation on a clear theoretical footing and show that this transform is able to embed the effect of the absolute position of the data stream into signature features in a unified and efficient way. The generated feature set is particularly useful in pattern recognition tasks, for its simplifying role in allowing the signature feature set to accommodate nonlinear functions of absolute and relative values.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/icpr48806.2021.9412642

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0002-9972-2809
Publisher:
IEEE Publisher's website
Volume:
2021
Pages:
4665-4672
Publication date:
2021-05-05
Event title:
25th International Conference on Pattern Recognition (ICPR 2020)
Event start date:
2021-01-10T00:00:00Z
Event end date:
2021-01-15T00:00:00Z
DOI:
EISBN:
978-1-7281-8808-9
ISSN:
1051-4651
ISBN:
978-1-7281-8809-6
Language:
English
Keywords:
Pubs id:
1119382
Local pid:
pubs:1119382
Deposit date:
2021-05-14

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