@inproceedings{SpiessFriesslichBluemmetal., author = {Spieß, Florian and Friesslich, Jonas and Bluemm, Daniel and Mast, Fabio and Vinokour, Dmitrij and Kounev, Samuel and Kaupp, Tobias and Strobel, Norbert}, title = {Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment}, series = {2021 20th International Conference on Advanced Robotics (ICAR)}, booktitle = {2021 20th International Conference on Advanced Robotics (ICAR)}, doi = {10.1109/ICAR53236.2021.9659355}, pages = {857 -- 864}, abstract = {To arrive at a realistic assessment of localization methods in terms of their performance in an industrial environment under various challenging conditions, we provide a benchmark to evaluate algorithms both for individual components as well as multi-sensor systems. For several sensor types, including wheel odometry, RGB cameras, RGB-D cameras, and LIDAR, potential issues were identified. The accuracy of wheel odometry, for example, when there are bumps on the track. For each sensor type, we explicitly chose a track for the benchmark dataset containing situations where the sensor fails to provide adequate measurements. Based on the acquired sensor data, localization can be achieved either using a single sensor information or sensor fusion. To help evaluate the output of associated localization algorithms, we provide a software to evaluate a set of metrics as part of the paper. An example application of the benchmark with state-of-the-art algorithms for each sensor is also provided.}, language = {en} } @article{SpiessReinhartStrobeletal., author = {Spiess, Florian and Reinhart, Lukas and Strobel, Norbert and Kaupp, Tobias and Kaiser, Dennis and Kounev, Samuel}, title = {People detection with depth silhouettes and convolutional neural networks on a mobile robot}, series = {Journal of Image and Graphics}, volume = {9}, journal = {Journal of Image and Graphics}, number = {4}, pages = {135 -- 139}, abstract = {This paper presents a novel people detection approach for mobile robot applications based on a combination of classical computer vision techniques and a state-of-the-art neural network. Our approach involves an RGB-D camera as an environmental sensor. The depth data is used to extract silhouettes around people. The RGB images are subsequently augmented with this border information before passing it to the neural network. Under challenging lighting conditions, our system was able to outperform the neural network trained on regular RGB data alone by a factor of two.}, language = {en} } @inproceedings{ShettyBirkholdStrobeletal., author = {Shetty, Karthik and Birkhold, Annette and Strobel, Norbert and Egger, Bernhard and Jaganathan, Srikrishna and Kowarschik, Markus and Maier, Andreas}, title = {Deep Learning Compatible Differentiable X-ray Projections for Inverse Rendering}, series = {Bildverarbeitung f{\"u}r die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9}, publisher = {Springer Fachmedien}, address = {Wiesbaden}, pages = {290 -- 295}, language = {en} } @article{ZhongAmrehnRavikumaretal., author = {Zhong, Xia and Amrehn, Mario and Ravikumar, Nishant and Chen, Shuqing and Strobel, Norbert and Birkhold, Annette and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Deep action learning enables robust 3D segmentation of body organs in various CT and MRI images}, series = {Scientific Reports}, volume = {11}, journal = {Scientific Reports}, number = {1}, doi = {10.1038/s41598-021-82370-6}, language = {en} } @article{BuschStrobelNobachetal., author = {Busch, Erik and Strobel, Norbert and Nobach, Kai and Bulitta, Clemens and Hirshfeld, John W. and Lin, Wu and de Abreu, Marcel Gama}, title = {Optimizing the innovation and development process of medical devices - a study based on angiographic equipment}, series = {Health and Technology}, volume = {11}, journal = {Health and Technology}, number = {3}, doi = {doi.org/10.1007/s12553-021-00537-7}, pages = {563 -- 574}, language = {en} } @article{RoserBirkholdPreuhsetal., author = {Roser, Philipp and Birkhold, Annette and Preuhs, Alexander and Syben, Christopher and Felsner, Lina and Hoppe, Elisabeth and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {X-ray Scatter Estimation Using Deep Splines}, series = {IEEE Transactions on Medical Imaging}, volume = {40}, journal = {IEEE Transactions on Medical Imaging}, number = {9}, pages = {2272 -- 2283}, language = {en} }