Michael Baumgartner

ZHAW School of Engineering
Forschungsschwerpunkt Angewandte Optik
Technikumstrasse 9
8400 Winterthur

+41 (0) 58 934 40 10
michael.baumgartner@zhaw.ch

Projekte

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (2024). Shedding light on the ageing of extra virgin olive oil : probing the impact of temperature with fluorescence spectroscopy and machine learning techniques. LWT - Food Science and Technology, 191(115679). https://doi.org/10.1016/j.lwt.2023.115679
Venturini, F., Fluri, S., & Baumgartner, M. (2023). Dataset of fluorescence EEM and UV spectroscopy data of olive oils during ageing. Data, 8(5), 81. https://doi.org/10.3390/data8050081
Venturini, F., Sperti, M., Michelucci, U., Herzig, I., Baumgartner, M., Caballero, J. P., Jimenez, A., & Deriu, M. A. (2021). Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques. Foods, 10(5), 1010. https://doi.org/10.3390/foods10051010
Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Dual oxygen and temperature luminescence learning sensor with parallel inference. Sensors, 20(17), 4886. https://doi.org/10.3390/s20174886
Michelucci, U., Baumgartner, M., & Venturini, F. (2019). Optical oxygen sensing with artificial intelligence. Sensors, 19(4), 777. https://doi.org/10.3390/s19040777
Venturini, F., Baumgartner, M., & Borisov, S. (2018). Mn4+-doped magnesium titanate : a promising phosphor for self-referenced optical temperature sensing. Sensors, 18(2/668). https://doi.org/10.3390/s18020668

Schriftliche Konferenzbeiträge, peer-reviewed

Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (2024). Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing [Conference paper]. In F. Berghmans & I. Zergioti (Eds.), Optical Sensing and Detection VIII (p. 129991F). SPIE. https://doi.org/10.1117/12.3016879
Michelucci, U., Fluri, S., Baumgartner, M., & Venturini, F. (2023). Deep learning super resolution for high-speed excitation emission matrix measurements [Conference paper]. In B. Jalali & K.-i. Kitayama (Eds.), AI and Optical Data Sciences IV (Vol. 12438). SPIE. https://doi.org/10.1117/12.2647589
Venturini, F., Michelucci, U., & Baumgartner, M. (2021). New approach for temperature-immune oxygen sensing based on Pt-TFPP [Conference paper]. OSA Technical Digest, SW5H. https://doi.org/10.1364/SENSORS.2021.SW5H.2
Venturini, F., Michelucci, U., & Baumgartner, M. (2021). Implementation of multi-task learning neural network architectures for robust industrial optical sensing [Conference poster]. In P. Lehmann, W. Osten, & A. Albertazzi Gonçalves Jr. (Eds.), Optical Measurement Systems for Industrial Inspection XII. Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2593469
Venturini, F., Michelucci, U., & Baumgartner, M. (2021). Implementation of multi-task learning neural network architectures for robust industrial optical sensing [Conference paper]. In P. Lehmann, W. Osten, & A. Albertazzi Gonçalves Jr. (Eds.), Optical Measurement Systems for Industrial Inspection XII (p. 117822H). Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2593469
Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks [Conference paper]. Proceedings Volume 11354 : Optical Sensing and Detection VI, 113541C. https://doi.org/10.1117/12.2554941
Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Deep-learning for multi-parameter luminescence sensing : demonstration of dual sensor. Proceedings Frontiers in Optics / Laser Science.
Venturini, F., Michelucci, U., & Baumgartner, M. (2020, January 27). Multi-task learning approach for optical luminescence sensing. Applied Machine Learning Days (AMLD), Lausanne, 25-29 January 2020.
Venturini, F., Baumgartner, M., & Michelucci, U. (2019). New approach for luminescence sensing based on machine learning [Conference paper]. In B. Jalali & K.-i. Kitayama (Eds.), Proceedings Volume 10937 : Optical Data Science II (Issue 109370H). SPIE. https://doi.org/10.1117/12.2508969
Venturini, F., Baumgartner, M., & Borisov, S. M. (2018). New opportunities for optical temperature sensing with Mn4+-doped magnesium titanate. Advanced Photonics 2018. https://doi.org/10.1364/BGPPM.2018.JTu2A.63

Mündliche Konferenzbeiträge und Abstracts

Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (2024, April 10). Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing. SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024. https://doi.org/10.1117/12.3016879
Venturini, F., Michelucci, U., & Baumgartner, M. (2021, July 21). New approach for temperature-immune oxygen sensing based on Pt-TFPP. OSA Optical Sensors and Sensing Congress, Online, 19-23 July 2021. https://osa.zoom.us/rec/play/MvNgUQyUZcCHsaYidUEieFhKJSC_0H951ohgwMQLgaJu2hOUG4Cp8c6EbckrxwSFPVgA4icXYkOKpYHl.bke5ll04aQIuRasd?continueMode=true&_x_zm_rtaid=rEeKPUbBRbuPidh8EtTeUQ.1630395453945.87ac6bdfd1c3781b0e74319831d7e46a&_x_zm_rhtaid=928
Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Deep-learning for multi-parameter luminescence sensing : demonstration of dual sensor. OSA Frontiers in Optics / Laser Science, Online, 14-17 September 2020.
Venturini, F., Michelucci, U., & Baumgartner, M. (2020, April 1). Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks. SPIE Photonics Europe, Digital Forum, France, 6 - 10 April 2020.
Venturini, F., & Baumgartner, M. (2019). New approach for luminescence sensing based on machine learning. SPIE OPTO, San Francisco, USA, 2-7 February 2019.

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