Evaluation of interest point detectors C Schmid, R Mohr, C Bauckhage International Journal of computer vision 37 (2), 151-172, 2000 | 2510 | 2000 |
Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems L Von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ... IEEE Transactions on Knowledge and Data Engineering 35 (1), 614-633, 2021 | 691 | 2021 |
The slashdot zoo: mining a social network with negative edges J Kunegis, A Lommatzsch, C Bauckhage Proceedings of the 18th international conference on World wide web, 741-750, 2009 | 575 | 2009 |
Comparing and evaluating interest points C Schmid, R Mohr, C Bauckhage Sixth International Conference on Computer Vision (IEEE Cat. No. 98CH36271 …, 1998 | 507 | 1998 |
Informed Haar-like Features Improve Pedestrian Detection S Zhang, C Bauckhage, A Cremers Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 405 | 2014 |
Insights into Internet Memes C Bauckhage Weblogs and Social Media 2011. ICWSM 2011. Fifth International AAAI …, 2011 | 367 | 2011 |
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine learning 102, 209-245, 2016 | 279 | 2016 |
Analyzing social bookmarking systems: A del. icio. us cookbook R Wetzker, C Zimmermann, C Bauckhage Proceedings of the ECAI 2008 Mining Social Data Workshop, 26-30, 2008 | 276 | 2008 |
Guns, swords and data: Clustering of player behavior in computer games in the wild A Drachen, R Sifa, C Bauckhage, C Thurau IEEE Conference on Computational Intelligence and Games, 163-170, 2012 | 240 | 2012 |
Predicting Player Churn in the Wild F Hadiji, R Sifa, A Drachen, C Thurau, K Kersting, C Bauckhage IEEE Conference on Computational Intelligence and Games, 2014 | 225 | 2014 |
Loveparade 2010: Automatic Video Analysis of a Crowd Disaster B Krausz, C Bauckhage Computer Vision and Image Understanding 116 (3), 307-319, 2012 | 223 | 2012 |
Combining machine learning and simulation to a hybrid modelling approach: Current and future directions L von Rueden, S Mayer, R Sifa, C Bauckhage, J Garcke Advances in Intelligent Data Analysis XVIII: 18th International Symposium on …, 2020 | 192 | 2020 |
Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis C Römer, M Wahabzada, A Ballvora, F Pinto, M Rossini, C Panigada, ... Functional Plant Biology 39 (11), 878-890, 2012 | 181 | 2012 |
Plant phenotyping using probabilistic topic models: uncovering the hyperspectral language of plants M Wahabzada, AK Mahlein, C Bauckhage, U Steiner, EC Oerke, ... Scientific reports 6 (1), 22482, 2016 | 149 | 2016 |
I tag, you tag: translating tags for advanced user models R Wetzker, C Zimmermann, C Bauckhage, S Albayrak Proceedings of the third ACM international conference on Web search and data …, 2010 | 148 | 2010 |
Clustering Game Behavior Data C Bauckhage, A Drachen, R Sifa Computational Intelligence and AI in Games, IEEE Transactions on 7 (3), 266-278, 2015 | 141 | 2015 |
Predicting purchase decisions in mobile free-to-play games R Sifa, F Hadiji, J Runge, A Drachen, K Kersting, C Bauckhage proceedings of the AAAI conference on artificial intelligence and …, 2015 | 134 | 2015 |
Metro maps of plant disease dynamics—automated mining of differences using hyperspectral images M Wahabzada, AK Mahlein, C Bauckhage, U Steiner, EC Oerke, ... Plos one 10 (1), e0116902, 2015 | 132 | 2015 |
Learning human-like movement behavior for computer games C Thurau, C Bauckage, G Sagerer | 129 | 2004 |
How Players Lose Interest in Playing a Game: An Empirical Study Based on Distributions of Total Playing Times C Bauckhage, K Kersting, R Sifa, C Thurau, A Drachen, A Canossa IEEE Conference on Computational Intelligence and Games, 2012 | 123 | 2012 |