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Alexander Freytag
Alexander Freytag
ZEISS, Corporate Research and Technology
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Année
Selecting Influential Examples: Active Learning with Expected Model Output Changes
A Freytag, E Rodner, J Denzler
European Conference on Computer Vision (ECCV), 2014
2652014
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
1672013
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
1562016
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
1322014
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
1182016
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
922021
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
742016
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
732015
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
712015
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
42*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
422018
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
352013
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
312012
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
26*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
262016
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
252017
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
222012
Intra-operative Brain Tumor Detection with Deep Learning-Optimized Hyperspectral Imaging
T Giannantonio, A Alperovich, P Semeraro, M Atzori, X Zhang, C Hauger, ...
arXiv preprint arXiv:2302.02884, 2023
152023
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
152016
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
152013
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