Pattern recognition: introduction, features, classifiers and principles J Beyerer, M Richter, M Nagel Walter de Gruyter GmbH & Co KG, 2017 | 56* | 2017 |
Facial expression classification on web images M Richter, T Gehrig, HK Ekenel Proceedings of the 21st International Conference on Pattern Recognition …, 2012 | 12 | 2012 |
Towards Collaborative Predictive Maintenance Leveraging Private Cross-Company Data M Mohr12, C Becker, R Möller, M Richter | 12* | |
Combining synthetic image acquisition and machine learning: Accelerated design and deployment of sorting systems MG Retzlaff, M Richter, T Längle, J Beyerer, C Dachsbacher Forum Bildverarbeitung, 49-61, 2016 | 10 | 2016 |
An approach to color-based sorting of bulk materials with automated estimation of system parameters M Richter, T Längle, J Beyerer tm-Technisches Messen 82 (3), 135-144, 2015 | 6 | 2015 |
Gaussian mixture trees for one class classification in automated visual inspection M Richter, T Längle, J Beyerer International Conference Image Analysis and Recognition, 341-351, 2017 | 5 | 2017 |
Knowing when you don't: Bag of visual words with reject option for automatic visual inspection of bulk materials M Richter, T Längle, J Beyerer 2016 23rd International Conference on Pattern Recognition (ICPR), 3079-3084, 2016 | 5 | 2016 |
Visual words for automated visual inspection of bulk materials M Richter, T Längle, J Beyerer 2015 14th IAPR International Conference on Machine Vision Applications (MVA …, 2015 | 5 | 2015 |
Optical filter selection for automatic visual inspection M Richter, J Beyerer IEEE Winter Conference on Applications of Computer Vision, 123-128, 2014 | 5 | 2014 |
Feature selection with a budget M Richter, G Maier, R Gruna, T Längle, J Beyerer World Congress on Electrical Engineering and Computer Systems and Science …, 2016 | 4 | 2016 |
Extending explicit shape regression with mixed feature channels and pose priors M Richter, H Gao, HK Ekenel IEEE Winter Conference on Applications of Computer Vision, 1013-1019, 2014 | 4 | 2014 |
Guided Linear Dimensionality Reduction by Stochastic Gradient Descent M Richter Proceedings of the 2015 Joint Workshop of Fraunhofer IOSB and Institute for …, 2016 | 3 | 2016 |
Parameter-learning for color sorting of bulk materials using genetic algorithms M Richter, J Beyerer Forum Bildverarbeitung, 107-118, 2014 | 3 | 2014 |
Large scale classification of spectral signatures M Richter, T Längle, J Beyerer tm-Technisches Messen 82 (12), 663-671, 2015 | 2 | 2015 |
Über lernende optische Inspektion am Beispiel der Schüttgutsortierung M Richter KIT Scientific Publishing, 2018 | 1 | 2018 |
Methods of learning discriminative features for automated visual inspection M Richter Proceedings of the 2014 Joint Workshop of Fraunhofer IOSB and Institute for …, 2015 | | 2015 |
Towards many-class classification of materials based on their spectral fingerprints M Richter, J Beyerer OCM 2015-Optical Characterization of Materials-conference proceedings, 103, 2015 | | 2015 |
From measurement to material–Preparing hyperspectral signatures for classification J Walocha, M Richter OCM 2015-Optical Characterization of Materials-conference proceedings, 137, 2015 | | 2015 |
Automatic Selection of Optical Filters for Classification in Hyperspectral Images M Richter Proceedings of the 2013 Joint Workshop of Fraunhofer IOSB and Institute for …, 2014 | | 2014 |
Simulation poröser Materialien M Richter | | 2009 |