Peer reviewed journal papers
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(2024): Fresh concrete properties from stereoscopic image sequences. PFG (2024), 517-529.
DOI: 10.1007/s41064-024-00303-0
Peer reviewed conference papers
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(2024): Image-based deep learning for the time-dependent prediction of fresh concrete properties. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-2-2024, pp. 145–152.
DOI: 10.5194/isprs-annals-X-2-2024-145-2024
Non-reviewed conference papers
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(2024): Selbstlernende Steuerungstechniken für die automatisierte Produktion robuster Ressourcenschutzbetone – Einblicke in das Forschungsprojekt ReCyCONtrol. cpi 02/24, p. 36-45. More info
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(2022): Digitization of the Concrete Production Chain using Computer Vision and Artificial Intelligence, fib proceedings no. 59, 6th fib Congress “Concrete Innovation for Sustainability,” 10 p. | File |
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(2022): Concrete 4.0 – Self-learning Digital Production Techniques for Sustainable Concrete - Beton 4.0 – Selbstlernende digitale Produktionstechniken für nachhaltige Betone, Proceedings of the 66th BetonTage, BFT-International, Vol. 88(6), 33-34. More info
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(2022): Image-based deep learning for rheology determination of Bingham fluids. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 711–720.
DOI: 10.5194/isprs-archives-XLIII-B2-2022-711-2022