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ORCIDErik Rodner
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2020 – today
- 2024
[c55]Frank Fuchs-Kittowski, Paul Schulze, Andreas Abecker, Jonas Lachowitzer, Stefan Lossow, Heino Rudolf, Erik Rodner:
Eine Methode für die Potenzialanalyse zur Identifikation von Anwendungsszenarien für Maschinelles Lernen. INFORMATIK 2024: 1127-1144- [c54]Andreas Abecker, Matthias Budde, Frank Fuchs-Kittowski, Janik Großmann, Werner Koch, Jonas Lachowitzer, Stefan Lossow, Erik Rodner, Heino Rudolf, Paul Schulze:
Zum Einsatz von Maschinellem Lernen in der Umweltverwaltung: Der Simplex4Learning Ansatz. INFORMATIK 2024: 1193-1206 - [i28]Ricardo Knauer, Erik Rodner:
Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications. CoRR abs/2405.07662 (2024) - [i27]Ricardo Knauer, Marvin Grimm, Erik Rodner:
PMLBmini: A Tabular Classification Benchmark Suite for Data-Scarce Applications. CoRR abs/2409.01635 (2024) - [i26]Ricardo Knauer, Mario Koddenbrock, Raphael Wallsberger, Nicholas M. Brisson, Georg N. Duda, Deborah Falla, David W. Evans, Erik Rodner:
"Oh LLM, I'm Asking Thee, Please Give Me a Decision Tree": Zero-Shot Decision Tree Induction and Embedding with Large Language Models. CoRR abs/2409.18594 (2024) - 2023
- [c53]Simon Reiß, Constantin Seibold, Alexander Freytag, Erik Rodner, Rainer Stiefelhagen:
Decoupled Semantic Prototypes enable learning from diverse annotation types for semi-weakly segmentation in expert-driven domains. CVPR 2023: 15495-15506 - [c52]Mohamed Riad Yagoubi, Seyed Ali Amirshahi, Steven Le Moan, Azeddine Beghdadi, Erik Rodner:
Blind Video Stabilization Quality Assessment based on convolutional LSTM. EUVIP 2023: 1-6 - [c51]Ricardo Knauer, Raphael Wallsberger, Marvin Grimm, Marian Bookhahn, Frank Neumann, Stephan Matzka, Erik Rodner
:
Foundations for applied artificial intelligence: enabling and supporting AI teaching and research. GI-Jahrestagung 2023: 353-356 - [c50]Ricardo Knauer, Erik Rodner:
Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective. KI 2023: 114-129 - [i25]Dennis Ritter, Mike Hemberger, Marc Hönig, Volker Stopp, Erik Rodner, Kristian Hildebrand:
CAD Models to Real-World Images: A Practical Approach to Unsupervised Domain Adaptation in Industrial Object Classification. CoRR abs/2310.04757 (2023) - [i24]Ricardo Knauer, Erik Rodner:
Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective. CoRR abs/2310.05464 (2023) - 2022
- [c49]Simon Reiß, Constantin Seibold, Alexander Freytag, Erik Rodner, Rainer Stiefelhagen:
Graph-Constrained Contrastive Regularization for Semi-weakly Volumetric Segmentation. ECCV (21) 2022: 401-419 - [c48]Dominik Probst, Hasnain Raza, Erik Rodner:
Evaluating Zero-Cost Active Learning for Object Detection. SEFM Workshops 2022: 38-47 - [i23]Dominik Probst, Hasnain Raza, Erik Rodner:
Evaluating Zero-cost Active Learning for Object Detection. CoRR abs/2212.04211 (2022) - 2021
- [c47]Simon Reiß, Constantin Seibold, Alexander Freytag, Erik Rodner, Rainer Stiefelhagen:
Every Annotation Counts: Multi-Label Deep Supervision for Medical Image Segmentation. CVPR 2021: 9532-9542 - [i22]Simon Reiß, Constantin Seibold, Alexander Freytag, Erik Rodner, Rainer Stiefelhagen:
Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation. CoRR abs/2104.13243 (2021) - 2020
- [j9]Marcel Simon, Erik Rodner, Trevor Darrell, Joachim Denzler:
The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization. IEEE Trans. Pattern Anal. Mach. Intell. 42(3): 749-763 (2020)
2010 – 2019
- 2019
- [j8]Björn Barz, Erik Rodner, Yanira Guanche Garcia, Joachim Denzler:
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1088-1101 (2019) - 2018
- [c46]Christoph Käding, Erik Rodner, Alexander Freytag, Oliver Mothes, Björn Barz, Joachim Denzler:
Active Learning for Regression Tasks with Expected Model Output Changes. BMVC 2018: 103 - [c45]Alexander Freytag, Vittorio Ferrari, Mario Fritz, Uwe Franke, Terrance E. Boult, Juergen Gall, Walter J. Scheirer, Angela Yao, Erik Rodner:
Workshop on Interactive and Adaptive Learning in an Open World. ECCV Workshops (6) 2018: 487-493 - [i21]Björn Barz, Erik Rodner, Yanira Guanche Garcia, Joachim Denzler:
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection. CoRR abs/1804.07091 (2018) - 2017
- [j7]Erik Rodner, Alexander Freytag, Paul Bodesheim, Björn Fröhlich, Joachim Denzler:
Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks. Int. J. Comput. Vis. 121(2): 253-280 (2017) - [c44]Marcel Simon, Yang Gao, Trevor Darrell, Joachim Denzler, Erik Rodner:
Generalized Orderless Pooling Performs Implicit Salient Matching. ICCV 2017: 4970-4979 - [i20]Marc Aubreville, Christian Knipfer, Nicolai Oetter, Christian Jaremenko, Erik Rodner, Joachim Denzler, Christopher Bohr, Helmut Neumann, Florian Stelzle, Andreas K. Maier:
Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning. CoRR abs/1703.01622 (2017) - [i19]Björn Barz, Erik Rodner, Christoph Käding, Joachim Denzler:
Fast Learning and Prediction for Object Detection using Whitened CNN Features. CoRR abs/1704.02930 (2017) - [i18]Marcel Simon, Yang Gao, Trevor Darrell, Joachim Denzler, Erik Rodner:
Generalized orderless pooling performs implicit salient matching. CoRR abs/1705.00487 (2017) - [i17]Talha Qaiser, Abhik Mukherjee, Chaitanya Reddy Pb, Sai Dileep Munugoti, Vamsi Tallam, Tomi Pitkäaho, Taina Lehtimäki, Thomas J. Naughton, Matt Berseth, Aníbal Pedraza, Ramakrishnan Mukundan, Matthew Smith, Abhir Bhalerao, Erik Rodner, Marcel Simon, Joachim Denzler, Chao-Hui Huang, Gloria Bueno, David R. J. Snead, Ian O. Ellis, Mohammad Ilyas, Nasir M. Rajpoot:
Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues. CoRR abs/1705.08369 (2017) - 2016
- [j6]Sergio Guadarrama, Erik Rodner, Kate Saenko, Trevor Darrell:
Understanding object descriptions in robotics by open-vocabulary object retrieval and detection. Int. J. Robotics Res. 35(1-3): 265-280 (2016) - [c43]Christoph Käding, Erik Rodner, Alexander Freytag, Joachim Denzler:
Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios. ACCV Workshops (3) 2016: 588-605 - [c42]Yerania Campos, Erik Rodner, Joachim Denzler, Humberto Sossa, Gonzalo Pajares:
Vegetation Segmentation in Cornfield Images Using Bag of Words. ACIVS 2016: 193-204 - [c41]Manuel Amthor, Erik Rodner, Joachim Denzler:
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets. BMVC 2016 - [c40]Erik Rodner, Marcel Simon, Robert B. Fisher, Joachim Denzler:
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches. BMVC 2016 - [c39]Jonas Jäger, Erik Rodner, Joachim Denzler, Viviane Wolff, Klaus Fricke-Neuderth:
SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos. CLEF (Working Notes) 2016: 481-489 - [c38]Alexander Freytag, Erik Rodner, Marcel Simon, Alexander Loos, Hjalmar S. Kühl, Joachim Denzler:
Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates. GCPR 2016: 51-63 - [c37]Christoph Käding, Alexander Freytag, Erik Rodner, Andrea Perino, Joachim Denzler:
Large-Scale Active Learning with Approximations of Expected Model Output Changes. GCPR 2016: 179-191 - [c36]Joachim Denzler, Erik Rodner, Marcel Simon:
Convolutional Neural Networks as a Computational Model for the Underlying Processes of Aesthetics Perception. ECCV Workshops (1) 2016: 871-887 - [c35]Christoph Käding, Erik Rodner, Alexander Freytag, Joachim Denzler:
Watch, Ask, Learn, and Improve: a lifelong learning cycle for visual recognition. ESANN 2016 - [i16]Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Neither Quick Nor Proper - Evaluation of QuickProp for Learning Deep Neural Networks. CoRR abs/1606.04333 (2016) - [i15]Manuel Amthor, Erik Rodner, Joachim Denzler:
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets. CoRR abs/1610.02850 (2016) - [i14]Erik Rodner, Marcel Simon, Robert B. Fisher, Joachim Denzler:
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches. CoRR abs/1610.06756 (2016) - [i13]Erik Rodner, Björn Barz, Yanira Guanche, Milan Flach, Miguel D. Mahecha, Paul Bodesheim, Markus Reichstein, Joachim Denzler:
Maximally Divergent Intervals for Anomaly Detection. CoRR abs/1610.06761 (2016) - [i12]Marcel Simon, Erik Rodner, Joachim Denzler:
ImageNet pre-trained models with batch normalization. CoRR abs/1612.01452 (2016) - [i11]Christoph Käding, Erik Rodner, Alexander Freytag, Joachim Denzler:
Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes. CoRR abs/1612.06129 (2016) - 2015
- [c34]Christoph Käding, Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Active learning and discovery of object categories in the presence of unnameable instances. CVPR 2015: 4343-4352 - [c33]Marcel Simon, Erik Rodner:
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks. ICCV 2015: 1143-1151 - [c32]Marcel Simon, Erik Rodner, Joachim Denzler:
Fine-grained classification of identity document types with only one example. MVA 2015: 126-129 - [c31]Johannes Rühle, Erik Rodner, Joachim Denzler:
Beyond thinking in common categories: Predicting obstacle vulnerability using large random codebooks. MVA 2015: 198-201 - [c30]Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding. VISAPP (2) 2015: 510-517 - [c29]Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Local Novelty Detection in Multi-class Recognition Problems. WACV 2015: 813-820 - [i10]Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding. CoRR abs/1502.06344 (2015) - [i9]Marcel Simon, Erik Rodner:
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks. CoRR abs/1504.08289 (2015) - [i8]Erik Rodner, Marcel Simon, Gunnar Brehm, Stephanie Pietsch, Johann-Wolfgang Wägele, Joachim Denzler:
Fine-grained Recognition Datasets for Biodiversity Analysis. CoRR abs/1507.00913 (2015) - [i7]Trevor Darrell, Marius Kloft, Massimiliano Pontil, Gunnar Rätsch, Erik Rodner:
Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). Dagstuhl Reports 5(4): 18-55 (2015) - 2014
- [b2]Herbert Süße, Erik Rodner:
Bildverarbeitung und Objekterkennung - Computer Vision in Industrie und Medizin. SpringerVieweg 2014, ISBN 978-3-8348-2605-3, pp. I-XVIII, 1-666 - [j5]Judy Hoffman, Erik Rodner, Jeff Donahue, Brian Kulis, Kate Saenko:
Asymmetric and Category Invariant Feature Transformations for Domain Adaptation. Int. J. Comput. Vis. 109(1-2): 28-41 (2014) - [c28]Marcel Simon, Erik Rodner, Joachim Denzler:
Part Detector Discovery in Deep Convolutional Neural Networks. ACCV (2) 2014: 162-177 - [c27]Daniel Haase, Erik Rodner, Joachim Denzler:
Instance-Weighted Transfer Learning of Active Appearance Models. CVPR 2014: 1426-1433 - [c26]Christoph Göring, Erik Rodner, Alexander Freytag, Joachim Denzler:
Nonparametric Part Transfer for Fine-Grained Recognition. CVPR 2014: 2489-2496 - [c25]Alexander Freytag, Erik Rodner, Trevor Darrell, Joachim Denzler:
Exemplar-Specific Patch Features for Fine-Grained Recognition. GCPR 2014: 144-156 - [c24]Alexander Freytag, Erik Rodner, Joachim Denzler:
Selecting Influential Examples: Active Learning with Expected Model Output Changes. ECCV (4) 2014: 562-577 - [c23]Daniel Goehring, Judy Hoffman, Erik Rodner, Kate Saenko, Trevor Darrell:
Interactive adaptation of real-time object detectors. ICRA 2014: 1282-1289 - [c22]Sergio Guadarrama, Erik Rodner, Kate Saenko, Ning Zhang, Ryan Farrell, Jeff Donahue, Trevor Darrell:
Open-vocabulary Object Retrieval. Robotics: Science and Systems 2014 - [i6]Björn Barz, Erik Rodner, Joachim Denzler:
ARTOS - Adaptive Real-Time Object Detection System. CoRR abs/1407.2721 (2014) - [i5]Alexander Freytag, Johannes Rühle, Paul Bodesheim, Erik Rodner, Joachim Denzler:
Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods. CoRR abs/1408.4692 (2014) - [i4]Marcel Simon, Erik Rodner, Joachim Denzler:
Part Detector Discovery in Deep Convolutional Neural Networks. CoRR abs/1411.3159 (2014) - 2013
- [j4]Björn Fröhlich, Erik Rodner, Michael Kemmler, Joachim Denzler:
Large-scale gaussian process multi-class classification for semantic segmentation and facade recognition. Mach. Vis. Appl. 24(5): 1043-1053 (2013) - [j3]Michael Kemmler, Erik Rodner, Esther-Sabrina Wacker, Joachim Denzler:
One-class classification with Gaussian processes. Pattern Recognit. 46(12): 3507-3518 (2013) - [c21]Jeff Donahue, Judy Hoffman, Erik Rodner, Kate Saenko, Trevor Darrell:
Semi-supervised Domain Adaptation with Instance Constraints. CVPR 2013: 668-675 - [c20]Paul Bodesheim, Alexander Freytag, Erik Rodner, Michael Kemmler, Joachim Denzler:
Kernel Null Space Methods for Novelty Detection. CVPR 2013: 3374-3381 - [c19]Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes. GCPR 2013: 282-291 - [c18]Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Approximations of Gaussian Process Uncertainties for Visual Recognition Problems. SCIA 2013: 182-194 - [c17]Judy Hoffman, Erik Rodner, Jeff Donahue, Kate Saenko, Trevor Darrell:
Efficient Learning of Domain-invariant Image Representations. ICLR (Poster) 2013 - [i3]Erik Rodner, Judy Hoffman, Jeff Donahue, Trevor Darrell, Kate Saenko:
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations. CoRR abs/1308.4200 (2013) - [i2]Christoph Göring, Alexander Freytag, Erik Rodner, Joachim Denzler:
Fine-grained Categorization - Short Summary of our Entry for the ImageNet Challenge 2012. CoRR abs/1310.4759 (2013) - 2012
- [c16]Björn Fröhlich, Erik Rodner, Joachim Denzler:
Semantic Segmentation with Millions of Features: Integrating Multiple Cues in a Combined Random Forest Approach. ACCV (1) 2012: 218-231 - [c15]Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels. ACCV (2) 2012: 511-524 - [c14]Paul Bodesheim, Erik Rodner, Alexander Freytag, Joachim Denzler:
Divergence-Based One-Class Classification Using Gaussian Processes. BMVC 2012: 1-11 - [c13]Björn Fröhlich, Erik Rodner, Joachim Denzler:
As Time Goes by - Anytime Semantic Segmentation with Iterative Context Forests. DAGM/OAGM Symposium 2012: 1-10 - [c12]Erik Rodner, Alexander Freytag, Paul Bodesheim, Joachim Denzler:
Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels. ECCV (4) 2012: 85-98 - [c11]Xiaoyan Jiang, Erik Rodner, Joachim Denzler:
Multi-person Tracking-by-Detection Based on Calibrated Multi-camera Systems. ICCVG 2012: 743-751 - [c10]Alexander Freytag, Björn Fröhlich, Erik Rodner, Joachim Denzler:
Efficient semantic segmentation with Gaussian processes and histogram intersection kernels. ICPR 2012: 3313-3316 - [i1]Erik Rodner:
Visual Transfer Learning: Informal Introduction and Literature Overview. CoRR abs/1211.1127 (2012) - 2011
- [b1]Erik Rodner:
Learning from Few Examples for Visual Recognition Problems. Friedrich Schiller University of Jena, Verlag Dr. Hut 2011, ISBN 978-3-8439-0249-6, pp. I-VI, 1-254 - [j2]Erik Rodner, Joachim Denzler:
Learning with few examples for binary and multiclass classification using regularization of randomized trees. Pattern Recognit. Lett. 32(2): 244-251 (2011) - [c9]Erik Rodner, Esther-Sabrina Wacker, Michael Kemmler, Joachim Denzler:
One-Class Classification for Anomaly Detection in Wire Ropes with Gaussian Processes in a Few Lines of Code. MVA 2011: 219-222 - [p1]Erik Rodner:
Lernen mit wenigen Beispielen für die visuelle Objekterkennung. Ausgezeichnete Informatikdissertationen 2011: 151-160 - 2010
- [c8]Michael Kemmler, Erik Rodner, Joachim Denzler:
One-Class Classification with Gaussian Processes. ACCV (2) 2010: 489-500 - [c7]Erik Rodner, Joachim Denzler:
One-Shot Learning of Object Categories Using Dependent Gaussian Processes. DAGM-Symposium 2010: 232-241 - [c6]Björn Fröhlich, Erik Rodner, Joachim Denzler:
A Fast Approach for Pixelwise Labeling of Facade Images. ICPR 2010: 3029-3032
2000 – 2009
- 2009
- [c5]Erik Rodner, Joachim Denzler:
Randomized Probabilistic Latent Semantic Analysis for Scene Recognition. CIARP 2009: 945-953 - [c4]Michael Kemmler, Erik Rodner, Joachim Denzler:
Global Context Extraction for Object Recognition Using a Combination of Range and Visual Features. Dyn3D 2009: 96-109 - [c3]Erik Rodner, Joachim Denzler:
Learning with Few Examples by Transferring Feature Relevance. DAGM-Symposium 2009: 252-261 - 2008
- [j1]Olaf Kähler, Erik Rodner, Joachim Denzler:
On fusion of range and intensity information using Graph-Cut for planar patch segmentation. Int. J. Intell. Syst. Technol. Appl. 5(3/4): 365-373 (2008) - [c2]Erik Rodner, Herbert Süße, Wolfgang Ortmann, Joachim Denzler:
Difference of Boxes Filters Revisited: Shadow Suppression and Efficient Character Segmentation. Document Analysis Systems 2008: 263-269 - [c1]Erik Rodner, Joachim Denzler:
Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees. VMV 2008: 159-168
Coauthor Index
[j9] [j8] [c46] [i21] [j7] [c44] [i20] [i19] [i18] [i17] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [i16] [i15] [i14] [i13] [i12] [i11] [c34] [c32] [c31] [c30] [c29] [i10] [i8] [c28] [c27] [c26] [c25] [c24] [i6] [i5] [i4] [j4] [j3] [c20] [c19] [c18] [i2] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [j2] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [j1] [c2] [c1]
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