DVS Edition Citation

Gorges, T, Davidson, P, Boeschen, M, Hotho, A & Merz, C. (2024). IMU airtime detection in snowboard halfpipe: U-net deep learning approach outperforms traditional threshold algorithms. Sensors, 24 (21), 6773. Zugriff am 22.01.2025 unter https://doi.org/10.3390/s24216773

APA (7th ed.) Citation

Gorges, T., Davidson, P., Boeschen, M., Hotho, A., & Merz, C. (2024). IMU airtime detection in snowboard halfpipe: U-net deep learning approach outperforms traditional threshold algorithms. Sensors, 24(21), 6773.

Chicago Style (17th ed.) Citation

Gorges, T., P. Davidson, M. Boeschen, A. Hotho, and C. Merz. "IMU Airtime Detection in Snowboard Halfpipe: U-net Deep Learning Approach Outperforms Traditional Threshold Algorithms." Sensors 24, no. 21 (2024): 6773.

MLA (9th ed.) Citation

Gorges, T., et al. "IMU Airtime Detection in Snowboard Halfpipe: U-net Deep Learning Approach Outperforms Traditional Threshold Algorithms." Sensors, vol. 24, no. 21, 2024, p. 6773.