Citations refer to the original publication, not to a Scieee localized version.
Beck, M., Layh, M., Nebauer, M., & Pinzer, B. R. (2022). A novel tracking system for the iron foundry field based on deep convolutional neural networks. Journal of Intelligent Manufacturing, 33(7), 2119–2128. https://doi.org/10.1007/s10845-022-01970-9
Beck, Michael, et al. “A novel tracking system for the iron foundry field based on deep convolutional neural networks.” Journal of Intelligent Manufacturing, vol. 33, no. 7, 2022, pp. 2119–2128. https://doi.org/10.1007/s10845-022-01970-9.
Beck, Michael, Michael Layh, Markus Nebauer, and Bernd R. Pinzer. “A novel tracking system for the iron foundry field based on deep convolutional neural networks.” Journal of Intelligent Manufacturing 33, no. 7 (2022): 2119–2128. https://doi.org/10.1007/s10845-022-01970-9.
Beck, M. et al. (2022) ‘A novel tracking system for the iron foundry field based on deep convolutional neural networks’, Journal of Intelligent Manufacturing, 33(7), pp. 2119–2128. Available at: https://doi.org/10.1007/s10845-022-01970-9.
M. Beck, M. Layh, M. Nebauer, and B. R. Pinzer, “A novel tracking system for the iron foundry field based on deep convolutional neural networks,” Journal of Intelligent Manufacturing, vol. 33, no. 7, pp. 2119–2128, 2022, doi: 10.1007/s10845-022-01970-9.
@article{beck2022novel,
author = {Beck, Michael and Layh, Michael and Nebauer, Markus and Pinzer, Bernd R.},
title = {A novel tracking system for the iron foundry field based on deep convolutional neural networks},
journal = {Journal of Intelligent Manufacturing},
year = {2022},
volume = {33},
number = {7},
pages = {2119--2128},
publisher = {New York, NY: Springer US,New York, NY: Springer US},
doi = {10.1007/s10845-022-01970-9},
url = {https://doi.org/10.1007/s10845-022-01970-9}
}
