---
_id: '29294'
author:
- first_name: Tobias
full_name: Nickchen, Tobias
id: '27340'
last_name: Nickchen
orcid: 0000-0001-8958-9330
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data
for Image Recognition of Additively Manufactured Parts. In: 2021 IEEE Winter
Conference on Applications of Computer Vision (WACV). IEEE; 2021. doi:10.1109/wacv48630.2021.00204'
apa: Nickchen, T., Heindorf, S., & Engels, G. (2021). Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts. 2021
IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv48630.2021.00204
bibtex: '@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={10.1109/wacv48630.2021.00204},
booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)},
publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor},
year={2021} }'
chicago: Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts.” In
2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
IEEE, 2021. https://doi.org/10.1109/wacv48630.2021.00204.
ieee: 'T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training
Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: 10.1109/wacv48630.2021.00204.'
mla: Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image
Recognition of Additively Manufactured Parts.” 2021 IEEE Winter Conference
on Applications of Computer Vision (WACV), IEEE, 2021, doi:10.1109/wacv48630.2021.00204.
short: 'T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on
Applications of Computer Vision (WACV), IEEE, 2021.'
date_created: 2022-01-12T10:31:42Z
date_updated: 2022-10-17T15:07:38Z
department:
- _id: '66'
- _id: '574'
doi: 10.1109/wacv48630.2021.00204
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
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
publication_status: published
publisher: IEEE
status: public
title: Generating Physically Sound Training Data for Image Recognition of Additively
Manufactured Parts
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '5822'
author:
- first_name: Daniel
full_name: Gaspers, Daniel
last_name: Gaspers
- first_name: Christoph
full_name: Knorr, Christoph
last_name: Knorr
- first_name: Tobias
full_name: Nickchen, Tobias
id: '27340'
last_name: Nickchen
orcid: 0000-0001-8958-9330
- first_name: Daniel
full_name: Nickchen, Daniel
last_name: Nickchen
- first_name: Barbel
full_name: Mertsching, Barbel
last_name: Mertsching
- first_name: Mahmoud A.
full_name: Mohamed, Mahmoud A.
last_name: Mohamed
citation:
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: 2018 IEEE International Symposium on Safety, Security, and
Rescue Robotics (SSRR). IEEE; 2018. doi:10.1109/ssrr.2018.8468658'
apa: Gaspers, D., Knorr, C., Nickchen, T., Nickchen, D., Mertsching, B., & Mohamed,
M. A. (2018). Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments
for Mobile Robot Applications. In 2018 IEEE International Symposium on Safety,
Security, and Rescue Robotics (SSRR). IEEE. https://doi.org/10.1109/ssrr.2018.8468658
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={10.1109/ssrr.2018.8468658},
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}
}'
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 2018 IEEE International
Symposium on Safety, Security, and Rescue Robotics (SSRR). IEEE, 2018. https://doi.org/10.1109/ssrr.2018.8468658.
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 2018 IEEE International Symposium on Safety, Security,
and Rescue Robotics (SSRR), 2018.
mla: Gaspers, Daniel, et al. “Real-Time Graph-Based 3D Reconstruction of Sparse
Feature Environments for Mobile Robot Applications.” 2018 IEEE International
Symposium on Safety, Security, and Rescue Robotics (SSRR), IEEE, 2018, doi:10.1109/ssrr.2018.8468658.
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.'
date_created: 2018-11-26T08:49:44Z
date_updated: 2022-01-06T07:02:43Z
department:
- _id: '66'
- _id: '534'
doi: 10.1109/ssrr.2018.8468658
language:
- iso: eng
publication: 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics
(SSRR)
publication_identifier:
isbn:
- '9781538655726'
publication_status: published
publisher: IEEE
status: public
title: Real-time Graph-Based 3D Reconstruction of Sparse Feature Environments for
Mobile Robot Applications
type: conference
user_id: '27340'
year: '2018'
...