MultiSegVA: Using visual analytics to segment biologging time series on 
multiple scales

Meschenmoser, P.; Buchmuller, J. F.; Seebacher, D.; Wikelski, Martin; Keim, D. A.

doi:10.1109/tvcg.2020.3030386

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MultiSegVA: Using visual analytics to segment biologging time series on multiple scales

Meschenmoser, P., Buchmuller, J. F., Seebacher, D., Wikelski, M., & Keim, D. A. (2021). MultiSegVA: Using visual analytics to segment biologging time series on multiple scales. IEEE Transactions on Visualization and Computer Graphics, 27(2), 1623-1633. doi:10.1109/tvcg.2020.3030386.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-73AB-6 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-73AC-5

Genre: Journal Article

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Creators:
Meschenmoser, P., Author
Buchmuller, J. F., Author
Seebacher, D., Author
Wikelski, Martin¹, Author
Keim, D. A., Author

Affiliations:
1Department of Migration, Max Planck Institute of Animal Behavior, Max Planck Society, ou_3054975

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Dates: Date issued: 2021-02-01

Publication Status: Issued

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Identifiers: Other: WOS:000613746500125
DOI: 10.1109/tvcg.2020.3030386
ISSN: 1077-2626

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Title: IEEE Transactions on Visualization and Computer Graphics

Source Genre: Journal

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Publ. Info: New York, NY : IEEE Computer Society

Pages: - Volume / Issue: 27 (2) Sequence Number: - Start / End Page: 1623 - 1633 Identifier: ISSN: 1077-2626
CoNE: https://pure.mpg.de/cone/journals/resource/954925605807