Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data
Hosseini B, Hammer B (2017)
Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
Kurzbeitrag Konferenz / Poster | Englisch
Download
BMVA_main.pdf
125.56 KB
Autor*in
Einrichtung
Erscheinungsjahr
2017
Konferenz
BMVA Symposium on Human Activity Recognition and Monitoring
Konferenzort
London
Konferenzdatum
2017-11-08 – 2017-11-08
Page URI
https://pub.uni-bielefeld.de/record/2919987
Zitieren
Hosseini B, Hammer B. Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
Hosseini, B., & Hammer, B. (2017). Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
Hosseini, Babak, and Hammer, Barbara. 2017. “Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data”. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London .
Hosseini, B., and Hammer, B. (2017).“Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data”. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
Hosseini, B., & Hammer, B., 2017. Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
B. Hosseini and B. Hammer, “Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data”, Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London, 2017.
Hosseini, B., Hammer, B.: Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London (2017).
Hosseini, Babak, and Hammer, Barbara. “Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data”. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London, 2017.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
Dieses Objekt ist durch das Urheberrecht und/oder verwandte Schutzrechte geschützt. [...]
Volltext(e)
Name
BMVA_main.pdf
125.56 KB
Access Level
Open Access
Zuletzt Hochgeladen
2019-09-06T09:18:59Z
MD5 Prüfsumme
a6ee2d301235e74805df2ea6d8f3aa98