Erik Rodner

According to our database1, Erik Rodner authored at least 73 papers between 2008 and 2021.

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Bibliography

2021
Every Annotation Counts: Multi-Label Deep Supervision for Medical Image Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

2019
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

2018
Workshop on Interactive and Adaptive Learning in an Open World.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Active Learning for Regression Tasks with Expected Model Output Changes.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks.
Int. J. Comput. Vis., 2017

Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues.
CoRR, 2017

Fast Learning and Prediction for Object Detection using Whitened CNN Features.
CoRR, 2017

Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning.
CoRR, 2017

Generalized Orderless Pooling Performs Implicit Salient Matching.
Proceedings of the IEEE International Conference on Computer Vision, 2017

2016
Understanding object descriptions in robotics by open-vocabulary object retrieval and detection.
Int. J. Robotics Res., 2016

ImageNet pre-trained models with batch normalization.
CoRR, 2016

Maximally Divergent Intervals for Anomaly Detection.
CoRR, 2016

Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes.
CoRR, 2016

Neither Quick Nor Proper - Evaluation of QuickProp for Learning Deep Neural Networks.
CoRR, 2016

Watch, Ask, Learn, and Improve: a lifelong learning cycle for visual recognition.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Convolutional Neural Networks as a Computational Model for the Underlying Processes of Aesthetics Perception.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Large-Scale Active Learning with Approximations of Expected Model Output Changes.
Proceedings of the Pattern Recognition - 38th German Conference, 2016

Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates.
Proceedings of the Pattern Recognition - 38th German Conference, 2016

SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos.
Proceedings of the Working Notes of CLEF 2016, 2016

Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches.
Proceedings of the British Machine Vision Conference 2016, 2016

Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets.
Proceedings of the British Machine Vision Conference 2016, 2016

Vegetation Segmentation in Cornfield Images Using Bag of Words.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2016

Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios.
Proceedings of the Computer Vision - ACCV 2016 Workshops, 2016

2015
Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152).
Dagstuhl Reports, 2015

Fine-grained Recognition Datasets for Biodiversity Analysis.
CoRR, 2015

Local Novelty Detection in Multi-class Recognition Problems.
Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision, 2015

Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding.
Proceedings of the VISAPP 2015, 2015

Fine-grained classification of identity document types with only one example.
Proceedings of the 14th IAPR International Conference on Machine Vision Applications, 2015

Beyond thinking in common categories: Predicting obstacle vulnerability using large random codebooks.
Proceedings of the 14th IAPR International Conference on Machine Vision Applications, 2015

Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Active learning and discovery of object categories in the presence of unnameable instances.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Asymmetric and Category Invariant Feature Transformations for Domain Adaptation.
Int. J. Comput. Vis., 2014

Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods.
CoRR, 2014

ARTOS - Adaptive Real-Time Object Detection System.
CoRR, 2014

Open-vocabulary Object Retrieval.
Proceedings of the Robotics: Science and Systems X, 2014

Interactive adaptation of real-time object detectors.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Selecting Influential Examples: Active Learning with Expected Model Output Changes.
Proceedings of the Computer Vision - ECCV 2014, 2014

Exemplar-Specific Patch Features for Fine-Grained Recognition.
Proceedings of the Pattern Recognition - 36th German Conference, 2014

Instance-Weighted Transfer Learning of Active Appearance Models.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Nonparametric Part Transfer for Fine-Grained Recognition.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Part Detector Discovery in Deep Convolutional Neural Networks.
Proceedings of the Computer Vision - ACCV 2014, 2014

Bildverarbeitung und Objekterkennung - Computer Vision in Industrie und Medizin.
SpringerVieweg, ISBN: 978-3-8348-2605-3, 2014

2013
One-class classification with Gaussian processes.
Pattern Recognit., 2013

Large-scale gaussian process multi-class classification for semantic segmentation and facade recognition.
Mach. Vis. Appl., 2013

Efficient Learning of Domain-invariant Image Representations
Proceedings of the 1st International Conference on Learning Representations, 2013

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations.
CoRR, 2013

Fine-grained Categorization - Short Summary of our Entry for the ImageNet Challenge 2012.
CoRR, 2013

Approximations of Gaussian Process Uncertainties for Visual Recognition Problems.
Proceedings of the Image Analysis, 18th Scandinavian Conference, 2013

Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes.
Proceedings of the Pattern Recognition - 35th German Conference, 2013

Semi-supervised Domain Adaptation with Instance Constraints.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Kernel Null Space Methods for Novelty Detection.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Visual Transfer Learning: Informal Introduction and Literature Overview
CoRR, 2012

Efficient semantic segmentation with Gaussian processes and histogram intersection kernels.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Multi-person Tracking-by-Detection Based on Calibrated Multi-camera Systems.
Proceedings of the Computer Vision and Graphics - International Conference, 2012

Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels.
Proceedings of the Computer Vision - ECCV 2012, 2012

As Time Goes by - Anytime Semantic Segmentation with Iterative Context Forests.
Proceedings of the Pattern Recognition, 2012

Divergence-Based One-Class Classification Using Gaussian Processes.
Proceedings of the British Machine Vision Conference, 2012

Semantic Segmentation with Millions of Features: Integrating Multiple Cues in a Combined Random Forest Approach.
Proceedings of the Computer Vision - ACCV 2012, 2012

Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels.
Proceedings of the Computer Vision, 2012

2011
Learning with few examples for binary and multiclass classification using regularization of randomized trees.
Pattern Recognit. Lett., 2011

One-Class Classification for Anomaly Detection in Wire Ropes with Gaussian Processes in a Few Lines of Code.
Proceedings of the IAPR Conference on Machine Vision Applications (IAPR MVA 2011), 2011

Lernen mit wenigen Beispielen für die visuelle Objekterkennung.
Proceedings of the Ausgezeichnete Informatikdissertationen 2011, 2011

Learning from Few Examples for Visual Recognition Problems.
Verlag Dr. Hut, ISBN: 978-3-8439-0249-6, 2011

2010
A Fast Approach for Pixelwise Labeling of Facade Images.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

One-Shot Learning of Object Categories Using Dependent Gaussian Processes.
Proceedings of the Pattern Recognition, 2010

One-Class Classification with Gaussian Processes.
Proceedings of the Computer Vision - ACCV 2010, 2010

2009
Learning with Few Examples by Transferring Feature Relevance.
Proceedings of the Pattern Recognition, 2009

Global Context Extraction for Object Recognition Using a Combination of Range and Visual Features.
Proceedings of the Dynamic 3D Imaging, DAGM 2009 Workshop, 2009

Randomized Probabilistic Latent Semantic Analysis for Scene Recognition.
Proceedings of the Progress in Pattern Recognition, 2009

2008
On fusion of range and intensity information using Graph-Cut for planar patch segmentation.
Int. J. Intell. Syst. Technol. Appl., 2008

Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees.
Proceedings of the 13th International Fall Workshop on Vision, Modeling, and Visualization, 2008

Difference of Boxes Filters Revisited: Shadow Suppression and Efficient Character Segmentation.
Proceedings of the Eighth IAPR International Workshop on Document Analysis Systems, 2008


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