LSTM self-supervision for detailed behavior analysis
Behavior analysis provides a crucial non-invasive and easily accessible diagnostic tool for biomedical research. A detailed analysis of posture changes during skilled motor tasks can reveal distinct functional deficits and their restoration during recovery. Our specific scenario is based on a neuros...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Chapter/Article Konferenzschrift |
| Sprache: | Englisch |
| Veröffentlicht: |
09 November 2017
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| In: |
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2017, Pages: 3747-3756 |
| DOI: | 10.1109/CVPR.2017.399 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1109/CVPR.2017.399
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| Verfasserangaben: | Biagio Brattoli, Uta Büchler, Anna-Sophia Wahl, Martin E. Schwab, Björn Ommer |
| Zusammenfassung: | Behavior analysis provides a crucial non-invasive and easily accessible diagnostic tool for biomedical research. A detailed analysis of posture changes during skilled motor tasks can reveal distinct functional deficits and their restoration during recovery. Our specific scenario is based on a neuroscientific study of rodents recovering from a large sensorimotor cortex stroke and skilled forelimb grasping is being recorded. |
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| Beschreibung: | Gesehen am 13.02.2018 |
| Beschreibung: | Online Resource |
| DOI: | 10.1109/CVPR.2017.399 |