Publikationen

Meyer, M., Langer, A., Mehltretter, M., Beyer, D., Coenen, M., Schack, T., Haist, M., Heipke, C. (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

Haist M., Heipke C., Beyer D., Coenen M., Schack T., Vogel C., Ponick A., Langer A. (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. | Datei |

Haist M., Scheydt J.C., Heipke C., Beyer D., Coenen M., Schack T., Ponick A, Langer A., Wiggenhagen M., Secieru E., Zwolinski M., Stahl T., Mittenbühler M., Rauls J., Weilacher F., Koppenhagen M., Mazanec O., Sachsenhauser B., Spenner L., Meyer R., Tholen H., Spörel F., Fuhrmann A., Moß M., Nieweler K. (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. Weitere Informationen

Ponick A., Langer A., Beyer D., Coenen M., Haist M., Heipke C. (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