| Transfer learning in a transductive setting M Rohrbach, S Ebert, B Schiele Advances in neural information processing systems 26, 2013 | 301 | 2013 |
| Weakly Supervised Recognition of Daily Life Activities with Wearable Sensors M Stikic, D Larlus, S Ebert, B Schiele Pattern Analysis and Machine Intelligence, IEEE Transactions on 33 (12 …, 2011 | 233 | 2011 |
| RALF - Reinforced Active Learning Formulation for Object Class Recognition S Ebert, M Fritz, B Schiele IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2012 | 143 | 2012 |
| Extracting structures in image collections for object recognition S Ebert, D Larlus, B Schiele Computer Vision–ECCV 2010, 720-733, 2010 | 44 | 2010 |
| Active metric learning for object recognition S Ebert, M Fritz, B Schiele Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium …, 2012 | 15 | 2012 |
| Semi-Supervised Learning on a Budget: Scaling up to Large Datasets S Ebert, M Fritz, B Schiele Asian Conference on Computer Vision (ACCV), 2012 | 15 | 2012 |
| Pick Your Neighborhood–Improving Labels and Neighborhood Structure for Label Propagation S Ebert, M Fritz, B Schiele Pattern Recognition, 152-162, 2011 | 12 | 2011 |
| Where next in object recognition and how much supervision do we need? S Ebert, B Schiele Advanced Topics in Computer Vision, 35-64, 2013 | 5 | 2013 |
| Semi-supervised learning for image classification S Ebert | 4 | 2012 |
| of Proceedings: Pattern Recognition: 33rd DAGM Symposium A Elhayek, M Welk, J Weickert Springer, 2011 | | 2011 |
| of Proceedings: Computer Vision-ECCV 2010: 11th European Conference on Computer Vision.-Pt. I S Ebert, D Larlus, B Schiele Springer, 2010 | | 2010 |
| Dirichlet Process Mixture Models for Object Category Recognition. S Ebert Informatiktage, 27-30, 2009 | | 2009 |
