Multivariate confidence calibration for object detection F Kuppers, J Kronenberger, A Shantia, A Haselhoff Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 136 | 2020 |
A vehicle detection system based on haar and triangle features A Haselhoff, A Kummert 2009 IEEE intelligent vehicles symposium, 261-266, 2009 | 114 | 2009 |
Inspect, understand, overcome: A survey of practical methods for ai safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 68 | 2022 |
Pedestrian crossing detecting as a part of an urban pedestrian safety system S Sichelschmidt, A Haselhoff, A Kummert, M Roehder, B Elias, K Berns 2010 IEEE Intelligent Vehicles Symposium, 840-844, 2010 | 39 | 2010 |
Radar-vision fusion for vehicle detection by means of improved haar-like feature and adaboost approach A Haselhoff, A Kummert, G Schneider 2007 15th European Signal Processing Conference, 2070-2074, 2007 | 37 | 2007 |
On visual crosswalk detection for driver assistance systems A Haselhoff, A Kummert 2010 IEEE Intelligent Vehicles Symposium, 883-888, 2010 | 32 | 2010 |
Radar-vision fusion with an application to car-following using an improved adaboost detection algorithm A Haselhoff, A Kummert, G Schneider 2007 IEEE Intelligent Transportation Systems Conference, 854-858, 2007 | 32 | 2007 |
Deep neural networks and data for automated driving: Robustness, uncertainty quantification, and insights towards safety T Fingscheidt, H Gottschalk, S Houben Springer Nature, 2022 | 29 | 2022 |
An evolutionary optimized vehicle tracker in collaboration with a detection system A Haselhoff, A Kummert 2009 12th International IEEE Conference on Intelligent Transportation …, 2009 | 29 | 2009 |
A signal theoretic approach to measure the influence of image resolution for appearance-based vehicle detection A Haselhoff, S Schauland, A Kummert 2008 IEEE Intelligent Vehicles Symposium, 822-827, 2008 | 24 | 2008 |
From black-box to white-box: examining confidence calibration under different conditions F Schwaiger, M Henne, F Küppers, FS Roza, K Roscher, A Haselhoff arXiv preprint arXiv:2101.02971, 2021 | 18 | 2021 |
Random forest on an embedded device for real-time machine state classification F Küppers, J Albers, A Haselhoff 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 18 | 2019 |
Parametric and multivariate uncertainty calibration for regression and object detection F Küppers, J Schneider, A Haselhoff European Conference on Computer Vision, 426-442, 2022 | 17 | 2022 |
Confidence calibration for object detection and segmentation F Küppers, A Haselhoff, J Kronenberger, J Schneider Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 13 | 2022 |
2D line filters for vision-based lane detection and tracking A Haselhoff, A Kummert 2009 International Workshop on Multidimensional (nD) Systems, 1-5, 2009 | 12 | 2009 |
Bayesian confidence calibration for epistemic uncertainty modelling F Küppers, J Kronenberger, J Schneider, A Haselhoff 2021 IEEE Intelligent Vehicles Symposium (IV), 466-472, 2021 | 11 | 2021 |
Multisensor data fusion for advanced driver assistance systems-the Active Safety Car project A Gavriilidis, T Schwerdtfeger, J Velten, S Schauland, L Höhmann, ... The 2011 International Workshop on Multidimensional (nD) Systems, 1-5, 2011 | 10 | 2011 |
Towards black-box explainability with Gaussian discriminant knowledge distillation A Haselhoff, J Kronenberger, F Kuppers, J Schneider Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 8 | 2021 |
Dependency decomposition and a reject option for explainable models J Kronenberger, A Haselhoff arXiv preprint arXiv:2012.06523, 2020 | 7 | 2020 |
Markov random field for image synthesis with an application to traffic sign recognition A Haselhoff, C Nunn, D Müller, M Meuter, L Roese-Koerner 2017 IEEE Intelligent Vehicles Symposium (IV), 1407-1412, 2017 | 6 | 2017 |