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On Invariance, Equivariance, Correlation and Convolution of Spherical Harmonic Representations for Scalar and Vectorial Data

  • The mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report gives an in-depth introduction to the theoretical foundation and practical implementation of SH representations, summarizing works on rotation invariant and equivariant features, as well as convolutions and exactThe mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report gives an in-depth introduction to the theoretical foundation and practical implementation of SH representations, summarizing works on rotation invariant and equivariant features, as well as convolutions and exact correlations of signals on spheres. In extension, these methods are then generalized from scalar SH representations to Vectorial Harmonics (VH), providing the same capabilities for 3d vector fields on spheres.show moreshow less

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Metadaten
Document Type:Article (unreviewed)
Zitierlink: https://opus.hs-offenburg.de/8235
Bibliografische Angaben
Title (English):On Invariance, Equivariance, Correlation and Convolution of Spherical Harmonic Representations for Scalar and Vectorial Data
Author:Janis KeuperStaff MemberORCiDGND
Year of Publication:2023
Publisher:Arxiv
First Page:1
Last Page:105
DOI:https://doi.org/10.48550/arXiv.2307.03311
Language:English
Inhaltliche Informationen
Institutes:Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019)
Forschung / IMLA - Institute for Machine Learning and Analytics
Institutes:Bibliografie
Tag:Deep Leaning
Formale Angaben
Relevance:Wiss. Zeitschriftenartikel unreviewed
Open Access: Open Access 
 Diamond 
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International
ArXiv Id:http://arxiv.org/abs/2307.03311v1