[{"date_updated":"2022-10-17T15:07:38Z","publication_status":"published","author":[{"id":"27340","full_name":"Nickchen, Tobias","first_name":"Tobias","last_name":"Nickchen","orcid":"0000-0001-8958-9330"},{"id":"11871","full_name":"Heindorf, Stefan","first_name":"Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf"},{"last_name":"Engels","first_name":"Gregor","full_name":"Engels, Gregor","id":"107"}],"title":"Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts","status":"public","year":"2021","doi":"10.1109/wacv48630.2021.00204","user_id":"11871","publisher":"IEEE","_id":"29294","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://openaccess.thecvf.com/content/WACV2021/papers/Nickchen_Generating_Physically_Sound_Training_Data_for_Image_Recognition_of_Additively_WACV_2021_paper.pdf"}],"project":[{"_id":"52","name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"citation":{"bibtex":"@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>}, booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)}, publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor}, year={2021} }","ama":"Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. In: <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. IEEE; 2021. doi:<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>","mla":"Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>, IEEE, 2021, doi:<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>.","chicago":"Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” In <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. IEEE, 2021. <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">https://doi.org/10.1109/wacv48630.2021.00204</a>.","short":"T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021.","ieee":"T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>.","apa":"Nickchen, T., Heindorf, S., &#38; Engels, G. (2021). Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">https://doi.org/10.1109/wacv48630.2021.00204</a>"},"publication":"2021 IEEE Winter Conference on Applications of Computer Vision (WACV)","oa":"1","department":[{"_id":"66"},{"_id":"574"}],"type":"conference","date_created":"2022-01-12T10:31:42Z"},{"doi":"10.1109/ssrr.2018.8468658","user_id":"27340","_id":"5822","language":[{"iso":"eng"}],"publisher":"IEEE","date_updated":"2022-01-06T07:02:43Z","publication_status":"published","author":[{"first_name":"Daniel","last_name":"Gaspers","full_name":"Gaspers, Daniel"},{"first_name":"Christoph","last_name":"Knorr","full_name":"Knorr, Christoph"},{"id":"27340","full_name":"Nickchen, Tobias","orcid":"0000-0001-8958-9330","first_name":"Tobias","last_name":"Nickchen"},{"first_name":"Daniel","last_name":"Nickchen","full_name":"Nickchen, Daniel"},{"full_name":"Mertsching, Barbel","last_name":"Mertsching","first_name":"Barbel"},{"full_name":"Mohamed, Mahmoud A.","first_name":"Mahmoud A.","last_name":"Mohamed"}],"publication_identifier":{"isbn":["9781538655726"]},"year":"2018","title":"Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications","status":"public","department":[{"_id":"66"},{"_id":"534"}],"type":"conference","date_created":"2018-11-26T08:49:44Z","citation":{"apa":"Gaspers, D., Knorr, C., Nickchen, T., Nickchen, D., Mertsching, B., &#38; Mohamed, M. A. (2018). Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications. In <i>2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)</i>. IEEE. <a href=\"https://doi.org/10.1109/ssrr.2018.8468658\">https://doi.org/10.1109/ssrr.2018.8468658</a>","ieee":"D. Gaspers, C. Knorr, T. Nickchen, D. Nickchen, B. Mertsching, and M. A. Mohamed, “Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications,” in <i>2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)</i>, 2018.","chicago":"Gaspers, Daniel, Christoph Knorr, Tobias Nickchen, Daniel Nickchen, Barbel Mertsching, and Mahmoud A. Mohamed. “Real-Time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications.” In <i>2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)</i>. IEEE, 2018. <a href=\"https://doi.org/10.1109/ssrr.2018.8468658\">https://doi.org/10.1109/ssrr.2018.8468658</a>.","short":"D. Gaspers, C. Knorr, T. Nickchen, D. Nickchen, B. Mertsching, M.A. Mohamed, in: 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), IEEE, 2018.","mla":"Gaspers, Daniel, et al. “Real-Time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications.” <i>2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)</i>, IEEE, 2018, doi:<a href=\"https://doi.org/10.1109/ssrr.2018.8468658\">10.1109/ssrr.2018.8468658</a>.","ama":"Gaspers D, Knorr C, Nickchen T, Nickchen D, Mertsching B, Mohamed MA. Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications. In: <i>2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)</i>. IEEE; 2018. doi:<a href=\"https://doi.org/10.1109/ssrr.2018.8468658\">10.1109/ssrr.2018.8468658</a>","bibtex":"@inproceedings{Gaspers_Knorr_Nickchen_Nickchen_Mertsching_Mohamed_2018, title={Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for Mobile Robot Applications}, DOI={<a href=\"https://doi.org/10.1109/ssrr.2018.8468658\">10.1109/ssrr.2018.8468658</a>}, booktitle={2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)}, publisher={IEEE}, author={Gaspers, Daniel and Knorr, Christoph and Nickchen, Tobias and Nickchen, Daniel and Mertsching, Barbel and Mohamed, Mahmoud A.}, year={2018} }"},"publication":"2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)"}]