Novelty Detection
Team
Violeta Teodora Trifunov, Maha Shadaydeh, Paul Bodesheim
Motivation

In many important learning tasks, training examples are often available for only one class. Learning in this scenario is difficult, since training examples from “outside” are not available at all. This problem is known as one-class classification (OCC), novelty detection, and outlier detection, to name just a few. Our work in this area addresses the use of methods for deriving a set of suitable OCC scores and to apply OCC in an incremental learning framework.

Publications
2021
Facial Behavior Analysis using 4D Curvature Statistics for Presentation Attack Detection
Martin Thümmel and Sven Sickert and Joachim Denzler.
IEEE International Workshop on Biometrics and Forensics (IWBF). Pages 1-6. 2021.
[bibtex] [web] [code] [abstract]
Investigating the Consistency of Uncertainty Sampling in Deep Active Learning
Niklas Penzel and Christian Reimers and Clemens-Alexander Brust and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 159-173. 2021.
[bibtex] [pdf] [web] [abstract]
Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning
Violeta Teodora Trifunov and Maha Shadaydeh and Bj\"orn Barz and Joachim Denzler.
IEEE International Conference on Machine Learning and Applications (ICMLA). Pages 166-172. 2021.
[bibtex] [pdf] [web] [abstract]
2019
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection
Björn Barz and Erik Rodner and Yanira Guanche Garcia and Joachim Denzler.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 41 (5) : pp. 1088-1101. 2019. (Pre-print published in 2018.)
[bibtex] [pdf] [web] [code] [abstract]
Attribution of Multivariate Extreme Events
Yanira Guanche and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2019.
[bibtex] [pdf] [abstract]
2018
Causality analysis of ecological time series: a time-frequency approach
Maha Shadaydeh and Yanira Guanche Garcia and Miguel Mahecha and Markus Reichstein and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2018.
[bibtex] [pdf]
Extreme anomaly event detection in biosphere using linear regression and a spatiotemporal MRF model
Yanira Guanche Garcia and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
Natural Hazards. pp. 1-19. 2018.
[bibtex] [pdf] [web] [abstract]
2017
Maximally Divergent Intervals for Extreme Weather Event Detection
Björn Barz and Yanira Guanche and Erik Rodner and Joachim Denzler.
MTS/IEEE OCEANS Conference Aberdeen. Pages 1-9. 2017.
[bibtex] [pdf] [abstract]
Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques
Milan Flach and Fabian Gans and Alexander Brenning and Joachim Denzler and Markus Reichstein and Erik Rodner and Sebastian Bathiany and Paul Bodesheim and Yanira Guanche and Sebasitan Sippel and Miguel D. Mahecha.
Earth System Dynamics. 8 (3) : pp. 677-696. 2017.
[bibtex] [pdf] [web] [abstract]
Biosphere Anomalies Detection by Regression Models
Yanira Guanche and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
Conference on Advances in Extreme Value Analysis and Application to Natural Hazards (EVAN). 2017.
[bibtex] [pdf]
2016
Lifelong Learning for Visual Recognition Systems
Alexander Freytag. 2016. ISBN 9783843929950
[bibtex] [pdf] [web]
Watch, Ask, Learn, and Improve: A Lifelong Learning Cycle for Visual Recognition
Christoph Käding and Erik Rodner and Alexander Freytag and Joachim Denzler.
European Symposium on Artificial Neural Networks (ESANN). Pages 381-386. 2016.
[bibtex] [pdf] [code] [presentation] [abstract]
Maximally Divergent Intervals for Anomaly Detection
Erik Rodner and Björn Barz and Yanira Guanche and Milan Flach and Miguel Mahecha and Paul Bodesheim and Markus Reichstein and Joachim Denzler.
ICML Workshop on Anomaly Detection (ICML-WS). 2016. Best Paper Award
[bibtex] [pdf] [web] [code] [abstract]
Using Statistical Process Control for detecting anomalies in multivariate spatiotemporal Earth Observations
Milan Flach and Miguel Mahecha and Fabian Gans and Erik Rodner and Paul Bodesheim and Yanira Guanche-Garcia and Alexander Brenning and Joachim Denzler and Markus Reichstein.
European Geosciences Union General Assembly (EGU): Abstract + Oral Presentation. 2016.
[bibtex] [pdf] [web] [abstract]
Hot spots of multivariate extreme anomalies in Earth observations
Milan Flach and Sebastian Sippel and Paul Bodesheim and Alexander Brenning and Joachim Denzler and Fabian Gans and Yanira Guanche and Markus Reichstein and Erik Rodner and Miguel D. Mahecha.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2016.
[bibtex] [web] [abstract]
Detecting Multivariate Biosphere Extremes
Yanira Guanche Garcia and Erik Rodner and Milan Flach and Sebastian Sippel and Miguel Mahecha and Joachim Denzler.
International Workshop on Climate Informatics (CI). Pages 9-12. 2016.
[bibtex] [web] [abstract]
2015
Active Learning and Discovery of Object Categories in the Presence of Unnameable Instances
Christoph Käding and Alexander Freytag and Erik Rodner and Paul Bodesheim and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 4343-4352. 2015.
[bibtex] [pdf] [web] [code] [presentation] [supplementary] [abstract]
Local Novelty Detection in Multi-class Recognition Problems
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 813-820. 2015.
[bibtex] [pdf] [web] [supplementary] [abstract]
2013
One-class Classification with Gaussian Processes
Michael Kemmler and Erik Rodner and Esther-Sabrina Wacker and Joachim Denzler.
Pattern Recognition. 46 : pp. 3507-3518. 2013.
[bibtex] [pdf]
Automatic Identification of Novel Bacteria using Raman Spectroscopy and Gaussian Processes
Michael Kemmler and Erik Rodner and Petra R\"osch and J\"urgen Popp and Joachim Denzler.
Analytica Chimica Acta. 794 : pp. 29-37. 2013.
[bibtex] [pdf] [web] [supplementary]
An Efficient Approximation for Gaussian Process Regression
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler. 2013. Technical Report TR-FSU-INF-CV-2013-01
[bibtex] [pdf]
Approximations of Gaussian Process Uncertainties for Visual Recognition Problems
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler.
Scandinavian Conference on Image Analysis (SCIA). Pages 182-194. 2013.
[bibtex] [pdf] [web] [abstract]
Kernel Null Space Methods for Novelty Detection
Paul Bodesheim and Alexander Freytag and Erik Rodner and Michael Kemmler and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 3374-3381. 2013.
[bibtex] [pdf] [web] [code] [presentation] [abstract]
2012
Lernen mit wenigen Beispielen für die visuelle Objekterkennung
Erik Rodner.
Ausgezeichnete Informatikdissertationen 2011. 2012. in german
[bibtex] [pdf] [web]
Divergence-Based One-Class Classification Using Gaussian Processes
Paul Bodesheim and Erik Rodner and Alexander Freytag and Joachim Denzler.
British Machine Vision Conference (BMVC). Pages 50.1-50.11. 2012.
[bibtex] [pdf] [web] [presentation] [abstract]
2011
One-Class Classification for Anomaly Detection in Wire Ropes with Gaussian Processes in a Few Lines of Code
Erik Rodner and Esther-Sabrina Wacker and Michael Kemmler and Joachim Denzler.
Machine Vision Applications (MVA). Pages 219-222. 2011.
[bibtex] [pdf]
2010
One-Class Classification with Gaussian Processes
Michael Kemmler and Erik Rodner and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). Pages 489-500. 2010.
[bibtex] [pdf] [presentation]