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
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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.
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