| Selecting Influential Examples: Active Learning with Expected Model Output Changes A Freytag, E Rodner, J Denzler European Conference on Computer Vision (ECCV), 2014 | 193 | 2014 |
| Kernel Null Space Methods for Novelty Detection P Bodesheim, A Freytag, E Rodner, M Kemmler, J Denzler IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3374--3381, 2013 | 145 | 2013 |
| Nonparametric part transfer for fine-grained recognition C Goring, E Rodner, A Freytag, J Denzler IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014 | 130 | 2014 |
| Fine-tuning Deep Neural Networks in Continuous Learning Scenarios C Käding, E Rodner, A Freytag, J Denzler ACCV Workshop on Interpretation and Visualization of Deep Neural Nets (ACCV-WS), 2016 | 106 | 2016 |
| Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates A Freytag, E Rodner, M Simon, A Loos, H Kühl, J Denzler German Conference on Pattern Recognition (GCPR), 2016 | 90 | 2016 |
| Active Learning and Discovery of Object Categories in the Presence of Unnameable Instances C Kading, A Freytag, E Rodner, P Bodesheim, J Denzler IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4343-4352, 2015 | 67 | 2015 |
| Local Novelty Detection in Multi-class Recognition Problems P Bodesheim, A Freytag, E Rodner, J Denzler IEEE Winter Conference on Applications of Computer Vision (WACV), 2015 | 65 | 2015 |
| Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes C Käding, E Rodner, A Freytag, J Denzler arXiv preprint arXiv:1612.06129, 2016 | 54 | 2016 |
| Every annotation counts: Multi-label deep supervision for medical image segmentation S Reiß, C Seibold, A Freytag, E Rodner, R Stiefelhagen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 46 | 2021 |
| Labeling examples that matter: Relevance-Based Active Learning with Gaussian Processes A Freytag, E Rodner, P Bodesheim, J Denzler German Conference on Pattern Recognition (GCPR), 282-291, 2013 | 34 | 2013 |
| Active Learning for Regression Tasks with Expected Model Output Changes–Supplementary Material C Käding, E Rodner, A Freytag, O Mothes, B Barz, J Denzler British Machine Vision Conference (BMVC), 2018 | 30* | 2018 |
| Active Learning for Regression Tasks with Expected Model Output Changes C Käding, E Rodner, A Freytag, O Mothes, B Barz, J Denzler British Machine Vision Conference (BMVC), 2018 | 30 | 2018 |
| Large-scale gaussian process classification with flexible adaptive histogram kernels E Rodner, A Freytag, P Bodesheim, J Denzler European Conference on Computer Vision (ECCV), 85-98, 2012 | 30 | 2012 |
| Finding the unknown: Novelty detection with extreme value signatures of deep neural activations A Schultheiss, C Käding, A Freytag, J Denzler Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017 | 23 | 2017 |
| Rapid uncertainty computation with gaussian processes and histogram intersection kernels A Freytag, E Rodner, P Bodesheim, J Denzler Asian Conference on Computer Vision (ACCV), 511-524, 2012 | 22 | 2012 |
| Large-scale Active Learning with Approximations of Expected Model Output Changes–Supplementary Material– C Käding, A Freytag, E Rodner, A Perino, J Denzler German Conference on Pattern Recognition (GCPR), 2016 | 21* | 2016 |
| Large-scale Active Learning with Approximations of Expected Model Output Changes C Käding, A Freytag, E Rodner, A Perino, J Denzler German Conference on Pattern Recognition (GCPR), 2016 | 21 | 2016 |
| I want to know more—efficient multi-class incremental learning using gaussian processes A Lütz, E Rodner, J Denzler Pattern recognition and image analysis 23, 402-407, 2013 | 14 | 2013 |
| Exemplar-Specific Patch Features for Fine-Grained Recognition A Freytag, E Rodner, T Darrell, J Denzler German Conference on Pattern Recognition (GCPR), 144-156, 2014 | 13 | 2014 |
| Watch, Ask, Learn, and Improve: A Lifelong Learning Cycle for Visual Recognition C Käding, E Rodner, A Freytag, J Denzler European Symposium on Artificial Neural Networks (ESANN), 2016 | 12 | 2016 |
Erik RodnerUniversity of Applied Sciences (HTW Berlin)Verified email at htw-berlin.de
