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Parsing human skeletons in an operating room.

, , , , , , , , , , , и . Mach. Vis. Appl., 27 (7): 1035-1046 (2016)

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Michael Kranzfelder

Ursula Kranzfelder

Dietmar Kranzfelder

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Ivo Kranzfelder

 

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Interdisziplinäre Studie über eine geeignete Mensch-Maschine-Schnittstelle für NOTES., , , , , , , и . CURAC, том 1477 из CEUR Workshop Proceedings, стр. 6-8. Innsbruck Medical University, (2013)Testsystem zur Erzeugung von künstlichen Rauch- und Nebelpartikeln für die Entwicklung von Bildoptimierungs-Algorithmen in der minimal-invasiven Chirurgie., , , , , и . CURAC, стр. 131-134. (2014)Reliability of sensor-based real-time workflow recognition in laparoscopic cholecystectomy., , , , , , , и . Int. J. Comput. Assist. Radiol. Surg., 9 (6): 941-948 (2014)Klinische Anwendung der sensor-basierten Workflow-Erkennung am Beispiel der laparoskopischen Cholezystektomie., , , , , и . CURAC, стр. 181-184. (2014)Surgical reporting for laparoscopic cholecystectomy based on phase annotation by a convolutional neural network (CNN) and the phenomenon of phase flickering: a proof of concept., , , , , , , , и . Int. J. Comput. Assist. Radiol. Surg., 17 (11): 1991-1999 (2022)A Field Test of 5G Enhanced Mobile Ultrasound with Network Slicing., , , , , , и . GLOBECOM (Workshops), стр. 1-6. IEEE, (2021)Random Forests for Phase Detection in Surgical Workflow Analysis., , , , , , и . IPCAI, том 8498 из Lecture Notes in Computer Science, стр. 148-157. Springer, (2014)A centralized data acquisition framework for operating theatres., , , , , и . HealthCom, стр. 1-5. IEEE, (2015)The TUM LapChole dataset for the M2CAI 2016 workflow challenge., , , , , и . CoRR, (2016)Parsing human skeletons in an operating room., , , , , , , , , и 2 other автор(ы). Mach. Vis. Appl., 27 (7): 1035-1046 (2016)