Classifying the Wear of Turning Tools with Neural Networks. - Bernhard Sick (ICANN, 1997)

The FFT butterfly operation in 4 processor cycles on a 24 bit fixed-point DSP with a pipelined multiplier. - Martin Grajcar; Bernhard Sick (ICASSP, 1997)

Monitoring the wear of cutting tools in CNC-lathes with artificial neural networks. - Bernhard Sick (ICASSP, 1997)

A framework for the graphical specification and execution of complex signal processing applications. - Andreas Sicheneder; Armin Bender; Erich Fuchs; Roland Mandl; Bernhard Sick (ICASSP, 1998)

Online tool wear monitoring in turning using time-delay neural networks. - Bernhard Sick (ICASSP, 1998)

On-line tool wear monitoring in turning using neural networks. - Bernhard Sick (Neural Comput. Appl., 1998)

Signalinterpretation mit neuronalen Netzen unter Nutzung von modellbasiertem Nebenwissen am Beispiel der Verschleißüberwachung von Werkzeugen in CNC-Drehmaschinen. - Bernhard Sick (1999)

Signalinterpretation mit Neuronalen Netzen unter Nutzung von modellbasiertem Nebenwissen am Beispiel der Verschleißüberwachung von Werkzeugen in CNC-Drehmaschinen. - Bernhard Sick (Ausgezeichnete Informatikdissertationen, 1999)

Multisensorfusion bei der Verarbeitung mikrosystembasierter Signale. - Bernhard Sick; Werner Grass; Klaus Donner (Informationstechnik Tech. Inform., 1999)

Recurrent and Non-Recurrent Dynamic Network Paradigms: A Case Study. - Walter Maydl; Bernhard Sick (IJCNN (6), 2000)

Towards a Specification Technique for Component-Based Measurement and Control Software for Embedded Systems. - Walter Maydl; Bernhard Sick; Werner Grass (EUROMICRO, 2002)

Fusion of hard and soft computing techniques in indirect, online tool wear monitoring. - Bernhard Sick (IEEE Trans. Syst. Man Cybern. Part C, 2002)

Fast and Efficient Training of RBF Networks. - Oliver Buchtala; Alexander Hofmann; Bernhard Sick (ICANN, 2003)

Intrusion Detection in Computer Networks with Neural and Fuzzy Classifiers. - Alexander Hofmann; Carsten Schmitz; Bernhard Sick (ICANN, 2003)

Evolutionary Optimisation of RBF Network Architectures in a Direct Marketing Application. - Peter Neumann; Bernhard Sick; Dirk Arndt; Wendy Gersten (ICANN, 2003)

A strategy for an efficient training of radial basis function networks for classification applications. - Oliver Buchtala; Peter Neumann; Bernhard Sick (IJCNN, 2003)

Fast and efficient second-order training of the dynamic neural network paradigm. - Christian Gruber; Bernhard Sick (IJCNN, 2003)

Evolutionary optimization of radial basis function networks for intrusion detection. - Alexander Hofmann; Bernhard Sick (IJCNN, 2003)

Calibration of self-organizing maps for classification tasks. - Claudia Bach; Stefan Bredl; Wolfgang Kossa; Bernhard Sick (SMC, 2003)

Processing short-term and long-term information with a combination of hardand soft-computing techniques. - Christian Gruber; Bernhard Sick (SMC, 2003)

Rule extraction from neural networks for intrusion detection in computer networks. - Alexander Hofmann; Carsten Schmitz; Bernhard Sick (SMC, 2003)

Architecture optimization of radial basis function networks with a combination of hard- and soft-computing techniques. - Manuel Klimek; Bernhard Sick (SMC, 2003)

Indirect On-Line Tool Wear Monitoring. - Bernhard Sick (Computationally Intelligent Hybrid Systems, 2004)

A comparison of first- and second-order training algorithms for dynamic neural networks. - Ferid Bajramovic; Christian Gruber; Bernhard Sick (IJCNN, 2004)

Feature selection for intrusion detection: an evolutionary wrapper approach. - Alexander Hofmann; Timo Horeis; Bernhard Sick (IJCNN, 2004)

Evolutionary optimization of radial basis function classifiers for data mining applications. - Oliver Buchtala; Manuel Klimek; Bernhard Sick (IEEE Trans. Syst. Man Cybern. Part B, 2005)

Emergence in Organic Computing Systems: Discussion of a Controversial Concept. - Christian Müller-Schloer; Bernhard Sick (ATC, 2006)

Online Signature Verification with New Time Series Kernels for Support Vector Machines. - Christian Gruber; Thiemo Gruber; Bernhard Sick (ICB, 2006)

Functional Knowledge Exchange Within an Intelligent Distributed System. - Oliver Buchtala; Bernhard Sick (ARCS, 2007)

Towards an Automated Analysis of Neuroleptics' Impact on Human Hand Motor Skills. - Matthias Dose; Christian Gruber; Ariane Grunz; Christian Hook; Jürgen Kempf; Georg Scharfenberg; Bernhard Sick (CIBCB, 2007)

Collaborative Knowledge Discovery & Data Mining: From Knowledge to Experience. - Timo Horeis; Bernhard Sick (CIDM, 2007)

Hazard Situation Prediction Using Spatially and Temporally Distributed Vehicle Sensor Information. - Thomas Schon; Bernhard Sick; Markus Strassberger (CIDM, 2007)

Goodness of Fit: Measures for a Fuzzy Classifier. - Oliver Buchtala; Bernhard Sick (FOCI, 2007)

Basic Technologies for Knowledge Transfer in Intelligent Systems. - Oliver Buchtala; Bernhard Sick (ALIFE, 2007)

A Source Routing Solution to Non-Transitive Connectivity Problems in Distributed Hash Tables. - Ivan Dedinski; Andreas Berl; Alexander Hofmann; Sebastian Heglmeier; Bernhard Sick; Hermann de Meer (ISCC, 2007)

A Novelty-Driven Approach to Intrusion Alert Correlation Based on Distributed Hash Tables. - Alexander Hofmann; Ivan Dedinski; Bernhard Sick; Hermann de Meer (ISCC, 2007)

Cooperative Keep-Alives: An Efficient Outage Detection Algorithm for P2P Overlay Networks. - Ivan Dedinski; Alexander Hofmann; Bernhard Sick (Peer-to-Peer Computing, 2007)

Editorial. - Klaus Waldschmidt; Jan Haase 001; Werner Grass; Bernhard Sick (J. Syst. Archit., 2007)

Fusion of soft and hard computing: multi-dimensional categorization of computationally intelligent hybrid systems. - Bernhard Sick; Seppo J. Ovaska (Neural Comput. Appl., 2007)

Controlled Emergence and Self-Organization. - Christian Müller-Schloer; Bernhard Sick (Organic Computing, 2008)

Comparing Evolvable Hardware to Conventional Classifiers for Electromyographic Prosthetic Hand Control. - Kyrre Glette; Jim Tørresen; Thiemo Gruber; Bernhard Sick; Paul Kaufmann; Marco Platzner (AHS, 2008)

Selected papers of the ARCS06 conference: an introduction. - Werner Grass; Bernhard Sick; Theo Ungerer; Klaus Waldschmidt (Pers. Ubiquitous Comput., 2008)

Learning by Teaching versus Learning by Doing: Knowledge Exchange in Organic Agent Systems. - Dominik Fisch; Martin Jänicke; Edgar Kalkowski; Bernhard Sick (IEEE IA, 2009)

Training of radial basis function classifiers with resilient propagation and variational Bayesian inference. - Dominik Fisch; Bernhard Sick (IJCNN, 2009)

Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems. - Tilmann Rabl; Andreas Lang; Thomas Hackl; Bernhard Sick; Harald Kosch (TPCTC, 2009)

Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks. - Daniel Andrade; Bernhard Sick (UAI, 2009)

Technical data mining with evolutionary radial basis function classifiers. - Markus Bauer; Oliver Buchtala; Timo Horeis; Ralf Kern; Bernhard Sick; Robert Wagner (Appl. Soft Comput., 2009)

Periodical switching between related goals for improving evolvability to a fixed goal in multi-objective problems. - Seppo J. Ovaska; Bernhard Sick; Alden H. Wright (Inf. Sci., 2009)

On-line motif detection in time series with SwiftMotif. - Erich Fuchs; Thiemo Gruber; Jiri Nitschke; Bernhard Sick (Pattern Recognit., 2009)

Processing Short-Term and Long-Term Information With a Combination of Polynomial Approximation Techniques and Time-Delay Neural Networks. - Erich Fuchs; Christian Gruber; Tobias Reitmaier; Bernhard Sick (IEEE Trans. Neural Networks, 2009)

Novelty-Aware Attack Recognition - Intrusion Detection with Organic Computing Techniques. - Dominik Fisch; Ferdinand Kastl; Bernhard Sick (DIPES/BICC, 2010)

All for one or one for all? Combining heterogeneous features for activity spotting. - Ulf Blanke; Bernt Schiele; Matthias Kreil; Paul Lukowicz; Bernhard Sick; Thiemo Gruber (PerCom Workshops, 2010)

Quantitative Emergence – A Refined Approach Based on Divergence Measures. - Dominik Fisch; Martin Jänicke; Bernhard Sick; Christian Müller-Schloer (SASO, 2010)

Temporal data mining using shape space representations of time series. - Erich Fuchs; Thiemo Gruber; Helmuth Pree; Bernhard Sick (Neurocomputing, 2010)

On the versatility of radial basis function neural networks: A case study in the field of intrusion detection. - Dominik Fisch; Alexander Hofmann; Bernhard Sick (Inf. Sci., 2010)

So near and yet so far: New insight into properties of some well-known classifier paradigms. - Dominik Fisch; Bernhard Kühbeck; Bernhard Sick; Seppo J. Ovaska (Inf. Sci., 2010)

Online Segmentation of Time Series Based on Polynomial Least-Squares Approximations. - Erich Fuchs; Thiemo Gruber; Jiri Nitschke; Bernhard Sick (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Online Signature Verification With Support Vector Machines Based on LCSS Kernel Functions. - Christian Gruber; Thiemo Gruber; Sebastian Krinninger; Bernhard Sick (IEEE Trans. Syst. Man Cybern. Part B, 2010)

Divergence Measures as a Generalised Approach to Quantitative Emergence. - Dominik Fisch; Martin Jänicke; Christian Müller-Schloer; Bernhard Sick (Organic Computing, 2011)

Collaborative Learning by Knowledge Exchange. - Dominik Fisch; Edgar Kalkowski; Bernhard Sick (Organic Computing, 2011)

Active classifier training with the 3DS strategy. - Tobias Reitmaier; Bernhard Sick (CIDM, 2011)

In Your Interest - Objective Interestingness Measures for a Generative Classifier. - Dominik Fisch; Edgar Kalkowski; Bernhard Sick; Seppo J. Ovaska (ICAART (1), 2011)

Online Intrusion Alert Aggregation with Generative Data Stream Modeling. - Alexander Hofmann; Bernhard Sick (IEEE Trans. Dependable Secur. Comput., 2011)

SwiftRule: Mining Comprehensible Classification Rules for Time Series Analysis. - Dominik Fisch; Thiemo Gruber; Bernhard Sick (IEEE Trans. Knowl. Data Eng., 2011)

Forecasting exchange rates with ensemble neural networks and ensemble K-PLS: A case study for the US Dollar per Indian Rupee. - Mark J. Embrechts; Christopher J. Gatti; Jonathan D. Linton; Thiemo Gruber; Bernhard Sick (IJCNN, 2012)

Learning from others: Exchange of classification rules in intelligent distributed systems. - Dominik Fisch; Martin Jänicke; Edgar Kalkowski; Bernhard Sick (Artif. Intell., 2012)

Handedness tests for preschool children: A novel approach based on graphics tablets and support vector machines. - Thiemo Gruber; Britta Meixner; Johann Prosser; Bernhard Sick (Appl. Soft Comput., 2012)

Techniques for knowledge acquisition in dynamically changing environments. - Dominik Fisch; Martin Jänicke; Edgar Kalkowski; Bernhard Sick (ACM Trans. Auton. Adapt. Syst., 2012)

A Concept for Securing Cyber-Physical Systems with Organic Computing Techniques. - Jörg Hähner; Stefan Rudolph; Sven Tomforde; Dominik Fisch; Bernhard Sick; Nils Kopal; Arno Wacker (ARCS Workshops, 2013)

Blazing Fast Time Series Segmentation Based on Update Techniques for Polynomial Approximations. - Andre Gensler; Thiemo Gruber; Bernhard Sick (ICDM Workshops, 2013)

Let us know your decision: Pool-based active training of a generative classifier with the selection strategy 4DS. - Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2013)

Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers. - Paul Kaufmann; Kyrre Glette; Thiemo Gruber; Marco Platzner; Jim Tørresen; Bernhard Sick (IEEE Trans. Evol. Comput., 2013)

Engineering and Mastering Interwoven Systems. - Sven Tomforde; Jörg Hähner; Hella Seebach; Wolfgang Reif; Bernhard Sick; Arno Wacker; Ingo Scholtes (ARCS Workshops, 2014)

Temporal data analytics based on eigenmotif and shape space representations of time series. - Andre Gensler; Bernhard Sick; Jens Willkomm (ChinaSIP, 2014)

Location based learning of user behavior for proactive recommender systems in car comfort functions. - Thomas Stone; Olga Birth; Andre Gensler; Andreas Huber; Martin Jänicke; Bernhard Sick (GI-Jahrestagung, 2014)

Pedestrian's Trajectory Forecast in Public Traffic with Artificial Neural Networks. - Michael Goldhammer; Konrad Doll; Ulrich Brunsmann; Andre Gensler; Bernhard Sick (ICPR, 2014)

Analysis on termination of pedestrians' gait at urban intersections. - Michael Goldhammer; Andreas Hubert; Sebastian Köhler 004; Klaus Zindler; Ulrich Brunsmann; Konrad Doll; Bernhard Sick (ITSC, 2014)

Novel Criteria to Measure Performance of Time Series Segmentation Techniques. - Andre Gensler; Bernhard Sick (LWA, 2014)

Dealing with human variability in motion based, wearable activity recognition. - Matthias Kreil; Bernhard Sick; Paul Lukowicz (PerCom Workshops, 2014)

Self-Adapting Multi-sensor Systems: A Concept for Self-Improvement and Self-Healing Techniques. - Martin Jänicke; Bernhard Sick; Paul Lukowicz; David Bannach (SASO Workshops, 2014)

"Know Thyself" - Computational Self-Reflection in Intelligent Technical Systems. - Sven Tomforde; Jörg Hähner; Sebastian von Mammen; Christian Gruhl; Bernhard Sick; Kurt Geihs (SASO Workshops, 2014)

Interwoven Systems. - Sven Tomforde; Jörg Hähner; Bernhard Sick (Inform. Spektrum, 2014)

On general purpose time series similarity measures and their use as kernel functions in support vector machines. - Helmuth Pree; Benjamin Herwig; Thiemo Gruber; Bernhard Sick; Klaus David; Paul Lukowicz (Inf. Sci., 2014)

Knowledge Fusion for Probabilistic Generative Classifiers with Data Mining Applications. - Dominik Fisch; Edgar Kalkowski; Bernhard Sick (IEEE Trans. Knowl. Data Eng., 2014)

A building block for awareness in technical systems: Online novelty detection and reaction with an application in intrusion detection. - Christian Gruhl; Bernhard Sick; Arno Wacker; Sven Tomforde; Jörg Hähner (iCAST, 2015)

A Mutual Influence Detection Algorithm for Systems with Local Performance Measurement. - Stefan Rudolph; Sven Tomforde; Bernhard Sick; Jörg Hähner (SASO, 2015)

Using Ontology-Based Similarity Measures to Find Training Data for Problems with Sparse Data. - Edgar Kalkowski; Bernhard Sick (SMC, 2015)

Fast Feature Extraction for Time Series Analysis Using Least-Squares Approximations with Orthogonal Basis Functions. - Andre Gensler; Thiemo Gruber; Bernhard Sick (TIME, 2015)

A Toolchain for Context Recognition: Automating the Investigation of a Multitude of Parameter Sets. - Andreas Jahn 002; Sian Lun Lau; Klaus David; Bernhard Sick (VTC Fall, 2015)

A New Vision of Collaborative Active Learning. - Adrian Calma; Tobias Reitmaier; Bernhard Sick; Paul Lukowicz (CoRR, 2015)

Transductive active learning - A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data. - Tobias Reitmaier; Adrian Calma; Bernhard Sick (Inf. Sci., 2015)

The responsibility weighted Mahalanobis kernel for semi-supervised training of support vector machines for classification. - Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2015)

Any problems? a wearable sensor-based platform for representational learning-analytics. - Gerald Pirkl; Peter Hevesi; Paul Lukowicz; Pascal Klein 002; Carina Heisel; Sebastian Gröber; Jochen Kuhn; Bernhard Sick (UbiComp Adjunct, 2016)

Lifelong Learning and Collaboration of Smart Technical Systems in Open-Ended Environments - Opportunistic Collaborative Interactive Learning. - Gernot Bahle; Adrian Calma; Jan Marco Leimeister; Paul Lukowicz; Sarah Oeste-Reiss; Tobias Reitmaier; Albrecht Schmidt 001; Bernhard Sick; Gerd Stumme; Katharina Anna Zweig (ICAC, 2016)

Towards Self-Improving Activity Recognition Systems Based on Probabilistic, Generative Models. - Martin Jänicke; Sven Tomforde; Bernhard Sick (ICAC, 2016)

Correlation of Ontology-Based Semantic Similarity and Human Judgement for a Domain Specific Fashion Ontology. - Edgar Kalkowski; Bernhard Sick (ICWE, 2016)

Combination of uncertain ordinal expert statements: The combination rule EIDMR and its application to low-voltage grid classification with SVM. - Sebastian Breker; Bernhard Sick (IJCNN, 2016)

Resp-kNN: A probabilistic k-nearest neighbor classifier for sparsely labeled data. - Adrian Calma; Tobias Reitmaier; Bernhard Sick (IJCNN, 2016)

Forecasting wind power - an ensemble technique with gradual coopetitive weighting based on weather situation. - Andre Gensler; Bernhard Sick (IJCNN, 2016)

Trajectory prediction of cyclists using a physical model and an artificial neural network. - Stefan Zernetsch; Sascha Kohnen; Michael Goldhammer; Konrad Doll; Bernhard Sick (Intelligent Vehicles Symposium, 2016)

Coping with variability in motion based activity recognition. - Matthias Kreil; Bernhard Sick; Paul Lukowicz (iWOAR, 2016)

Towards Autonomous Self-Tests at Runtime. - Henner Heck; Stefan Rudolph; Christian Gruhl; Arno Wacker; Jörg Hähner; Bernhard Sick; Sven Tomforde (FAS*W@SASO/ICCAC, 2016)

Deep Learning for solar power forecasting - An approach using AutoEncoder and LSTM Neural Networks. - Andre Gensler; Janosch Henze; Bernhard Sick; Nils Raabe (SMC, 2016)

An analog ensemble-based similarity search technique for solar power forecasting. - Andre Gensler; Bernhard Sick; Vitali Pankraz (SMC, 2016)

A review of deterministic error scores and normalization techniques for power forecasting algorithms. - Andre Gensler; Bernhard Sick; Stephan Vogt (SSCI, 2016)

Design and optimization of an autonomous feature selection pipeline for high dimensional, heterogeneous feature spaces. - Bernhard Schlegel; Bernhard Sick (SSCI, 2016)

Detecting Novel Processes with CANDIES - An Holistic Novelty Detection Technique based on Probabilistic Models. - Christian Gruhl; Bernhard Sick (CoRR, 2016)

Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions. - Christian Gruhl; Bernhard Sick (CoRR, 2016)

Towards automation of knowledge understanding: An approach for probabilistic generative classifiers. - Dominik Fisch; Christian Gruhl; Edgar Kalkowski; Bernhard Sick; Seppo J. Ovaska (Inf. Sci., 2016)

Quantitative Robustness - A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems. - Jan Kantert; Sven Tomforde; Christian Müller-Schloer; Sarah Edenhofer; Bernhard Sick (ICAART (1), 2017)

Measuring Self-organisation at Runtime - A Quantification Method based on Divergence Measures. - Sven Tomforde; Jan Kantert; Bernhard Sick (ICAART (1), 2017)

Dealing with Class Imbalance the Scalable Way: Evaluation of Various Techniques Based on Classification Grade and Computational Complexity. - Bernhard Schlegel; Bernhard Sick (ICDM Workshops, 2017)

On Methodological and Technological Challenges for Proactive Health Management in Smart Homes. - Klaus-Hendrik Wolf; Tobias Dehling; Reinhold Haux; Bernhard Sick; Ali Sunyaev; Sven Tomforde (ICIMTH, 2017)

Cooperative starting intention detection of cyclists based on smart devices and infrastructure. - Maarten Bieshaar; Stefan Zernetsch; Malte Depping; Bernhard Sick; Konrad Doll (ITSC, 2017)

Cyclists' starting behavior at intersections. - Andreas Hubert; Stefan Zernetsch; Konrad Doll; Bernhard Sick (Intelligent Vehicles Symposium, 2017)

Simulation of Annotators for Active Learning: Uncertain Oracles. - Adrian Calma; Bernhard Sick (IAL@PKDD/ECML, 2017)

Identifying Representative Load Time Series for Load Flow Calculations. - Janosch Henze; Tanja Kneiske; Martin Braun 002; Bernhard Sick (DARE@PKDD/ECML, 2017)

Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. - Daniel Kottke; Adrian Calma; Denis Huseljic; Georg Krempl; Bernhard Sick (IAL@PKDD/ECML, 2017)

Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms. - Adrian Calma; Daniel Kottke; Bernhard Sick; Sven Tomforde (FAS*W@SASO/ICCAC, 2017)

Model-predictive planning for autonomous vehicles anticipating intentions of vulnerable road users by artificial neural networks. - Jan Eilbrecht; Maarten Bieshaar; Stefan Zernetsch; Konrad Doll; Bernhard Sick; Olaf Stursberg (SSCI, 2017)

Probabilistic wind power forecasting: A multi-scheme ensemble technique with gradual coopetitive soft gating. - Andre Gensler; Bernhard Sick (SSCI, 2017)

Self-Adaptation of Activity Recognition Systems to New Sensors. - David Bannach; Martin Jänicke; Vitor F. Rey; Sven Tomforde; Bernhard Sick; Paul Lukowicz (CoRR, 2017)

Organic Computing in the Spotlight. - Sven Tomforde; Bernhard Sick; Christian Müller-Schloer (CoRR, 2017)

Starting Movement Detection of Cyclists Using Smart Devices. - Maarten Bieshaar; Malte Depping; Jan Schneegans; Bernhard Sick (DSAA, 2018)

Leveraging the Potentials of Dedicated Collaborative Interactive Learning: Conceptual Foundations to Overcome Uncertainty by Human-Machine Collaboration. - Adrian Calma; Sarah Oeste-Reiß; Bernhard Sick; Jan Marco Leimeister (HICSS, 2018)

Hijacked Smart Devices - Methodical Foundations for Autonomous Theft Awareness based on Activity Recognition and Novelty Detection. - Martin Jänicke; Viktor Schmidt; Bernhard Sick; Sven Tomforde; Paul Lukowicz (ICAART (2), 2018)

Smart Device Stealing and CANDIES. - Martin Jänicke; Viktor Schmidt; Bernhard Sick; Sven Tomforde; Paul Lukowicz; Jörn Schmeißing (ICAART (Revised Selected Papers), 2018)

Active Learning With Realistic Data - A Case Study. - Adrian Calma; Moritz Stolz; Daniel Kottke; Sven Tomforde; Bernhard Sick (IJCNN, 2018)

Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. - Marek Herde; Daniel Kottke; Adrian Calma; Maarten Bieshaar; Stephan Deist; Bernhard Sick (IJCNN, 2018)

The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning. - Daniel Kottke; Adrian Calma; Denis Huseljic; Christoph Sandrock; George Kachergis; Bernhard Sick (IJCNN, 2018)

Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. - Günther Reitberger; Maarten Bieshaar; Stefan Zernetsch; Konrad Doll; Bernhard Sick; Erich Fuchs (ITSC, 2018)

Radar-based Feature Design and Multiclass Classification for Road User Recognition. - Nicolas Scheiner; Nils Appenrodt; Jürgen Dickmann; Bernhard Sick (Intelligent Vehicles Symposium, 2018)

Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network. - Stefan Zernetsch; Viktor Kress; Bernhard Sick; Konrad Doll (Intelligent Vehicles Symposium, 2018)

Gestaltungsraum für proaktive Smart Homes zur Gesundheitsförderung. - Theresa Kromat; Tobias Dehling; Reinhold Haux; Christoph Peters 001; Bernhard Sick; Sven Tomforde; Klaus-Hendrik Wolf; Ali Sunyaev (MKWI, 2018)

Towards Cooperative Self-adapting Activity Recognition. - Andreas Jahn 002; Sven Tomforde; Michel Morold; Klaus David; Bernhard Sick (PECCS, 2018)

Sampling Strategies for Representative Time Series in Load Flow Calculations. - Janosch Henze; Stephan Kutzner; Bernhard Sick (DARE@PKDD/ECML, 2018)

Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. - Christian Gruhl; Sven Tomforde; Bernhard Sick (FAS*W@SASO/ICAC, 2018)

Security Issues in Self-Improving System Integration - Challenges and Solution Strategies. - Henner Heck; Bernhard Sick; Sven Tomforde (FAS*W@SASO/ICAC, 2018)

Coopetitive Soft Gating Ensemble. - Jens Schreiber; Maarten Bieshaar; Andre Gensler; Bernhard Sick; Stephan Deist (FAS*W@SASO/ICAC, 2018)

Human Pose Estimation in Real Traffic Scenes. - Viktor Kress; Janis Jung; Stefan Zernetsch; Konrad Doll; Bernhard Sick (SSCI, 2018)

Hosting capacity of low-voltage grids for distributed generation: Classification by means of machine learning techniques. - Sebastian Breker; Jan Rentmeister; Bernhard Sick; Martin Braun 002 (Appl. Soft Comput., 2018)

Highly Automated Learning for Improved Active Safety of Vulnerable Road Users. - Maarten Bieshaar; Günther Reitberger; Viktor Kreß; Stefan Zernetsch; Konrad Doll; Erich Fuchs; Bernhard Sick (CoRR, 2018)

Quantifying the Influences on Probabilistic Wind Power Forecasts. - Jens Schreiber; Bernhard Sick (CoRR, 2018)

Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence. - Maarten Bieshaar; Günther Reitberger; Stefan Zernetsch; Bernhard Sick; Erich Fuchs; Konrad Doll (CoRR, 2018)

Self-Adaptive Multi-Sensor Activity Recognition Systems Based on Gaussian Mixture Models. - Martin Jänicke; Bernhard Sick; Sven Tomforde (Informatics, 2018)

Collaborative Interactive Learning. - Bernhard Sick; Sarah Oeste-Reiß; Albrecht Schmidt 001; Sven Tomforde; Katharina Anna Zweig (Inform. Spektrum, 2018)

Semi-supervised active learning for support vector machines: A novel approach that exploits structure information in data. - Adrian Calma; Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2018)

Novelty detection with CANDIES: a holistic technique based on probabilistic models. - Christian Gruhl; Bernhard Sick (Int. J. Mach. Learn. Cybern., 2018)

Performing event detection in time series with SwiftEvent: an algorithm with supervised learning of detection criteria. - Andre Gensler; Bernhard Sick (Pattern Anal. Appl., 2018)

Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness. - Sven Tomforde; Jan Kantert; Christian Müller-Schloer; Sebastian Bödelt; Bernhard Sick (Trans. Comput. Collect. Intell., 2018)

Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble. - Maarten Bieshaar; Stefan Zernetsch; Andreas Hubert; Bernhard Sick; Konrad Doll (IEEE Trans. Intell. Veh., 2018)

Early Pedestrian Movement Detection Using Smart Devices Based on Human Activity Recognition. - Diego Botache; Dandan Liu; Maarten Bieshaar; Bernhard Sick (GI-Jahrestagung (Workshops), 2019)

Using grid supporting flexibility in electricity distribution networks. - Immanuel König; Erik Heilmann; Janosch Henze; Klaus David; Heike Wetzel; Bernhard Sick (GI-Jahrestagung, 2019)

Start Intention Detection of Cyclists using an LSTM Network. - Viktor Kress; Janis Jung; Stefan Zernetsch; Konrad Doll; Bernhard Sick (GI-Jahrestagung (Workshops), 2019)

Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. - Jens Schreiber; Artjom Buschin; Bernhard Sick (GI-Jahrestagung, 2019)

Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. - Jens Schreiber; Maik Jessulat; Bernhard Sick (ICANN (3), 2019)

Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. - Christoph Sandrock; Marek Herde; Adrian Calma; Daniel Kottke; Bernhard Sick (IJCNN, 2019)

Pose Based Start Intention Detection of Cyclists. - Viktor Kress; Janis Jung; Stefan Zernetsch; Konrad Doll; Bernhard Sick (ITSC, 2019)

A Multi-Stage Clustering Framework for Automotive Radar Data. - Nicolas Scheiner; Nils Appenrodt; Jürgen Dickmann; Bernhard Sick (ITSC, 2019)

Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles. - Nicolas Scheiner; Nils Appenrodt; Jürgen Dickmann; Bernhard Sick (IV, 2019)

Trajectory Forecasts with Uncertainties of Vulnerable Road Users by Means of Neural Networks. - Stefan Zernetsch; Hannes Reichert; Viktor Kress; Konrad Doll; Bernhard Sick (IV, 2019)

Pose Based Trajectory Forecast of Vulnerable Road Users. - Viktor Kress; Stefan Zernetsch; Konrad Doll; Bernhard Sick (SSCI, 2019)

Limitations of Assessing Active Learning Performance at Runtime. - Daniel Kottke; Jim Schellinger; Denis Huseljic; Bernhard Sick (CoRR, 2019)

Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. - Tom Hanika; Marek Herde; Jochen Kuhn; Jan Marco Leimeister; Paul Lukowicz; Sarah Oeste-Reiß; Albrecht Schmidt 001; Bernhard Sick; Gerd Stumme; Sven Tomforde; Katharina Anna Zweig (CoRR, 2019)

Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS. - Nicolas Scheiner; Nils Appenrodt; Jürgen Dickmann; Bernhard Sick (CoRR, 2019)

Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices. - Nicolas Scheiner; Stefan Haag; Nils Appenrodt; Bharanidhar Duraisamy; Jürgen Dickmann; Martin Fritzsche; Bernhard Sick (CoRR, 2019)

Normal-Wishart Clustering for Novelty Detection. - Christian Gruhl; Jörn Schmeißing; Sven Tomforde; Bernhard Sick (ACSOS Companion, 2020)

A Swarm-fleet Infrastructure as a Scenario for Proactive, Hybrid Adaptation of System Behaviour. - Sven Tomforde; Christian Gruhl; Bernhard Sick (ACSOS Companion, 2020)

Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar. - Nicolas Scheiner; Florian Kraus; Fangyin Wei; Buu Phan; Fahim Mannan; Nils Appenrodt; Werner Ritter; Jürgen Dickmann; Klaus Dietmayer; Bernhard Sick; Felix Heide (CVPR, 2020)

Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification? - Nicolas Scheiner; Ole Schumann; Florian Kraus; Nils Appenrodt; Jürgen Dickmann; Bernhard Sick (FUSION, 2020)

Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning. - Christian Haase-Schütz; Rainer Stal; Heinz Hertlein; Bernhard Sick (ICPR, 2020)

Novelty Based Driver Identification on RR Intervals from ECG Data. - Florian Heidecker; Christian Gruhl; Bernhard Sick (ICPR Workshops (4), 2020)

Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. - Florian Heidecker; Abdul Hannan; Maarten Bieshaar; Bernhard Sick (ICPR Workshops (4), 2020)

Multi-Annotator Probabilistic Active Learning. - Marek Herde; Daniel Kottke; Denis Huseljic; Bernhard Sick (ICPR, 2020)

Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. - Denis Huseljic; Bernhard Sick; Marek Herde; Daniel Kottke (ICPR, 2020)

Pose Based Trajectory Forecast of Vulnerable Road Users Using Recurrent Neural Networks. - Viktor Kress; Stefan Zernetsch; Konrad Doll; Bernhard Sick (ICPR Workshops (1), 2020)

Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. - Jan Schneegans; Maarten Bieshaar; Florian Heidecker; Bernhard Sick (ICPR Workshops (4), 2020)

Emerging Relation Network and Task Embedding for Multi-Task Regression Problems. - Jens Schreiber; Bernhard Sick (ICPR, 2020)

Image Sequence Based Cyclist Action Recognition Using Multi-Stream 3D Convolution. - Stefan Zernetsch; Steven Schreck; Viktor Kress; Konrad Doll; Bernhard Sick (ICPR, 2020)

Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks. - Yujiang He; Janosch Henze; Bernhard Sick (IJCNN, 2020)

Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. - Tuan Pham Minh; Daniel Kottke; Anna Tsarenko; Christian Gruhl; Bernhard Sick (IJCNN, 2020)

Pose Based Action Recognition of Vulnerable Road Users Using Recurrent Neural Networks. - Viktor Kress; Steven Schreck; Stefan Zernetsch; Konrad Doll; Bernhard Sick (SSCI, 2020)

Trust Your Model: Iterative Label Improvement and Robust Training by Confidence Based Filtering and Dataset Partitioning. - Christian Haase-Schütz; Rainer Stal; Heinz Hertlein; Bernhard Sick (CoRR, 2020)

Extended Coopetitive Soft Gating Ensemble. - Stephan Deist; Jens Schreiber; Maarten Bieshaar; Bernhard Sick (CoRR, 2020)

Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets. - Maarten Bieshaar; Jens Schreiber; Stephan Vogt; André Gensler; Bernhard Sick (CoRR, 2020)

Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning. - Michael Goldhammer; Sebastian Köhler 004; Stefan Zernetsch; Konrad Doll; Bernhard Sick; Klaus Dietmayer (IEEE Trans. Intell. Transp. Syst., 2020)

Towards Highly Automated Machine-Learning-Empowered Monitoring of Motor Test Stands. - Diego Botache; Florian Bethke; Martin Hardieck; Maarten Bieshaar; Ludwig Brabetz; Mohamed Ayeb; Peter Zipf; Bernhard Sick (ACSOS, 2021)

AI - Based On The Fly Design of Experiments in Physics and Engineering. - Kristina Dingel; A. Liehr; M. Vogel; S. Degener; David Meier; Thoralf Niendorf; Arno Ehresmann; Bernhard Sick (ACSOS-C, 2021)

Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders. - Abdul Hannan; Christian Gruhl; Bernhard Sick (CSR, 2021)

Out-of-Distribution Detection and Generation Using Soft Brownian Offset Sampling and Autoencoders. - Felix Möller; Diego Botache; Denis Huseljic; Florian Heidecker; Maarten Bieshaar; Bernhard Sick (CVPR Workshops, 2021)

Description of Corner Cases in Automated Driving: Goals and Challenges. - Daniel Bogdoll; Jasmin Breitenstein; Florian Heidecker; Maarten Bieshaar; Bernhard Sick; Tim Fingscheidt; J. Marius Zöllner (ICCVW, 2021)

About the Ambiguity of Data Augmentation for 3D Object Detection in Autonomous Driving. - Matthias Reuse; Martin Simon; Bernhard Sick (ICCVW, 2021)

Toward Application of Continuous Power Forecasts in a Regional Flexibility Market. - Yujiang He; Zhixin Huang; Bernhard Sick (IJCNN, 2021)

Smart Infrastructure: A Research Junction. - Manuel Hetzel; Hannes Reichert; Konrad Doll; Bernhard Sick (ISC2, 2021)

Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. - Hannes Reichert; Lukas Lang; Kevin Rösch; Daniel Bogdoll; Konrad Doll; Bernhard Sick; Hans-Christian Reuss; Christoph Stiller; J. Marius Zöllner (ISC2, 2021)

Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information. - Stefan Zernetsch; Oliver Trupp; Viktor Kress; Konrad Doll; Bernhard Sick (ISC2, 2021)

An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving. - Florian Heidecker; Jasmin Breitenstein; Kevin Rösch; Jonas Löhdefink; Maarten Bieshaar; Christoph Stiller; Tim Fingscheidt; Bernhard Sick (IV, 2021)

Probabilistic VRU Trajectory Forecasting for Model-Predictive Planning A Case Study: Overtaking Cyclists. - Jan Schneegans; Jan Eilbrecht; Stefan Zernetsch; Maarten Bieshaar; Konrad Doll; Olaf Stursberg; Bernhard Sick (IV Workshops, 2021)

A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. - Maarten Bieshaar; Marek Herde; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2021)

Uncertainty and Utility Sampling with Pre-Clustering. - Zhixin Huang; Yujiang He; Stephan Vogt; Bernhard Sick (IAL@PKDD/ECML, 2021)

Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast. - Jens Schreiber; Stephan Vogt; Bernhard Sick (ECML/PKDD (4), 2021)

Cyclist Motion State Forecasting - Going beyond Detection. - Maarten Bieshaar; Stefan Zernetsch; Katharina Riepe; Konrad Doll; Bernhard Sick (SSCI, 2021)

A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. - Marek Herde; Denis Huseljic; Bernhard Sick; Adrian Calma (IEEE Access, 2021)

CLeaR: An Adaptive Continual Learning Framework for Regression Tasks. - Yujiang He; Bernhard Sick (CoRR, 2021)

Cyclist Intention Detection: A Probabilistic Approach. - Stefan Zernetsch; Hannes Reichert; Viktor Kress; Konrad Doll; Bernhard Sick (CoRR, 2021)

Probabilistic Active Learning for Active Class Selection. - Daniel Kottke; Georg Krempl; Marianne Stecklina; Cornelius Styp von Rekowski; Tim Sabsch; Tuan Pham Minh; Matthias Deliano; Myra Spiliopoulou; Bernhard Sick (CoRR, 2021)

Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses. - Kristina Dingel; Thorsten Otto; Lutz Marder; Lars Funke; Arne Held; Sara Savio; Andreas Hans; Gregor Hartmann; David Meier; Jens Viefhaus; Bernhard Sick; Arno Ehresmann; et al. (CoRR, 2021)

Towards Organic Distribution Systems - The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management. - Inga Löser; Martin Braun 002; Christian Gruhl; Jan-Hendrik Menke; Bernhard Sick; Sven Tomforde (CoRR, 2021)

AdaPT: Adaptable Particle Tracking for spherical microparticles in lab on chip systems. - Kristina Dingel; Rico Huhnstock; André Knie; Arno Ehresmann; Bernhard Sick (Comput. Phys. Commun., 2021)

Novelty detection in continuously changing environments. - Christian Gruhl; Bernhard Sick; Sven Tomforde (Future Gener. Comput. Syst., 2021)

Hybride Wissensarbeit. - Sarah Oeste-Reiß; Eva A. C. Bittner; Izabel Cvetkovic; Andreas Günther; Jan Marco Leimeister; Lucas Memmert; Anja Ott; Bernhard Sick; Kathrin Wolter (Inform. Spektrum, 2021)

Toward optimal probabilistic active learning using a Bayesian approach. - Daniel Kottke; Marek Herde; Christoph Sandrock; Denis Huseljic; Georg Krempl; Bernhard Sick (Mach. Learn., 2021)

Pedestrians and Cyclists in Road Traffic: Trajectories, 3D Poses and Semantic Maps. - Viktor Kress; Stefan Zernetsch; Maarten Bieshaar; Günther Reitberger; Erich Fuchs; Konrad Doll; Bernhard Sick (Zenodo, 2021)

Aschaffenburg Pose Dataset. - Viktor Kress; Stefan Zernetsch; Hannes Reichert; Manuel Hetzel; Maarten Bieshaar; Günther Reitberger; Erich Fuchs; Konrad Doll; Bernhard Sick (Zenodo, 2021)

Self-Aware Microsystems. - Christian Gruhl; Sven Tomforde; Bernhard Sick (ACSOS-C, 2022)

NDNET: A Unified Framework for Anomaly and Novelty Detection. - Jens Decke; Jörn Schmeißing; Diego Botache; Maarten Bieshaar; Bernhard Sick; Christian Gruhl (ARCS, 2022)

Generating Synthetic Time Series for Machine-Learning-Empowered Monitoring of Electric Motor Test Benches. - Tobias Westmeier; Diego Botache; Maarten Bieshaar; Bernhard Sick (DSAA, 2022)

Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. - Chandana Priya Nivarthi; Stephan Vogt; Bernhard Sick (ICMLA, 2022)

A Holistic View on Probabilistic Trajectory Forecasting - Case Study. Cyclist Intention Detection. - Stefan Zernetsch; Hannes Reichert; Viktor Kress; Konrad Doll; Bernhard Sick (IV, 2022)

A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning. - Marek Herde; Denis Huseljic; Jelena Mitrovic; Michael Granitzer; Bernhard Sick (IAL@PKDD/ECML, 2022)

A Stopping Criterion for Transductive Active Learning. - Daniel Kottke; Christoph Sandrock; Georg Krempl; Bernhard Sick (ECML/PKDD (4), 2022)

Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources. - Lukas Rauch; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2022)

A Practical Evaluation of Active Learning Approaches for Object Detection. - Jan Schneegans; Maarten Bieshaar; Bernhard Sick (IAL@PKDD/ECML, 2022)

Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving. - Kevin Rösch; Florian Heidecker; Julian Truetsch; Kamil Kowol; Clemens Schicktanz; Maarten Bieshaar; Bernhard Sick; Christoph Stiller (SSCI, 2022)

Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning. - Yujiang He; Zhixin Huang; Bernhard Sick (CoRR, 2022)

Synthetic Photovoltaic and Wind Power Forecasting Data. - Stephan Vogt; Jens Schreiber; Bernhard Sick (CoRR, 2022)

Model Selection, Adaptation, and Combination for Deep Transfer Learning through Neural Networks in Renewable Energies. - Jens Schreiber; Bernhard Sick (CoRR, 2022)

A Review of Uncertainty Calibration in Pretrained Object Detectors. - Denis Huseljic; Marek Herde; Mehmet Muejde; Bernhard Sick (CoRR, 2022)

Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. - Marek Herde; Zhixin Huang; Denis Huseljic; Daniel Kottke; Stephan Vogt; Bernhard Sick (CoRR, 2022)

Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. - Christian Krupitzer; Christian Gruhl; Bernhard Sick; Sven Tomforde (Inf. Softw. Technol., 2022)

Social Machines. - Claude Draude; Christian Gruhl; Gerrit Hornung; Jonathan Kropf; Jörn Lamla; Jan Marco Leimeister; Bernhard Sick; Gerd Stumme (Inform. Spektrum, 2022)

Efficient SVDD sampling with approximation guarantees for the decision boundary. - Adrian Englhardt; Holger Trittenbach; Daniel Kottke; Bernhard Sick; Klemens Böhm (Mach. Learn., 2022)

Stream-based active learning for sliding windows under the influence of verification latency. - Tuan Pham; Daniel Kottke; Georg Krempl; Bernhard Sick (Mach. Learn., 2022)

Self- Integration and Agent Compatibility. - Christian Gruhl; Bernhard Sick (ACSOS-C, 2023)

Leveraging Repeated Unlabelled Noisy Measurements to Augment Supervised Learning. - Birk Martin Magnussen; Claudius Stern; Bernhard Sick (CIIS, 2023)

Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. - Christoph Sandrock; Marek Herde; Daniel Kottke; Bernhard Sick (DS, 2023)

Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering. - Matthias Aßenmacher; Lukas Rauch; Jann Goschenhofer; Andreas Stephan; Bernd Bischl; Benjamin Roth 001; Bernhard Sick (IAL@PKDD/ECML, 2023)

Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning. - Marek Herde; Denis Huseljic; Bernhard Sick; Ulrich Bretschneider; Sarah Oeste-Reiß (IAL@PKDD/ECML, 2023)

Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. - Zhixin Huang; Yujiang He; Marek Herde; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2023)

Role of Hyperparameters in Deep Active Learning. - Denis Huseljic; Marek Herde; Paul Hahn; Bernhard Sick (IAL@PKDD/ECML, 2023)

Height Change Feature Based Free Space Detection. - Steven Schreck; Hannes Reichert; Manuel Hetzel; Konrad Doll; Bernhard Sick (ICCMA, 2023)

What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving. - Jasmin Breitenstein; Florian Heidecker; Maria Lyssenko; Daniel Bogdoll; Maarten Bieshaar; J. Marius Zöllner; Bernhard Sick; Tim Fingscheidt (ICCV (Workshops), 2023)

DADO - Low-Cost Query Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (ICMLA, 2023)

Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding. - Chandana Priya Nivarthi; Bernhard Sick (ICMLA, 2023)

Context Information for Corner Case Detection in Highly Automated Driving. - Florian Heidecker; Tobias Susetzky; Erich Fuchs; Bernhard Sick (ITSC, 2023)

The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset. - Manuel Hetzel; Hannes Reichert; Günther Reitberger; Erich Fuchs; Konrad Doll; Bernhard Sick (IV, 2023)

Sensor Equivariance by LiDAR Projection Images. - Hannes Reichert; Manuel Hetzel; Steven Schreck; Konrad Doll; Bernhard Sick (IV, 2023)

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. - Lukas Rauch; Matthias Aßenmacher; Denis Huseljic; Moritz Wirth; Bernd Bischl; Bernhard Sick (ECML/PKDD (1), 2023)

Dataset of a parameterized U-bend flow for Deep Learning Applications. - Jens Decke; Olaf Wünsch; Bernhard Sick (CoRR, 2023)

Sampling-based Uncertainty Estimation for an Instance Segmentation Network. - Florian Heidecker; Ahmad El-Khateeb; Bernhard Sick (CoRR, 2023)

DADO - Low-Cost Selection Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (CoRR, 2023)

Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis. - Diego Botache; Kristina Dingel; Rico Huhnstock; Arno Ehresmann; Bernhard Sick (CoRR, 2023)

Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (CoRR, 2023)

Active Label Refinement for Semantic Segmentation of Satellite Images. - Tuan Pham Minh; Jayan Wijesingha; Daniel Kottke; Marek Herde; Denis Huseljic; Bernhard Sick; Michael Wachendorf; Thomas Esch (CoRR, 2023)

Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation. - Diego Botache; Jens Decke; Winfried Ripken; Abhinay Dornipati; Franz Götz-Hahn; Mohamed Ayeb; Bernhard Sick (CoRR, 2023)

Multi-annotator Deep Learning: A Probabilistic Framework for Classification. - Marek Herde; Denis Huseljic; Bernhard Sick (Trans. Mach. Learn. Res., 2023)

Context-aware recommendations for extended electric vehicle battery lifetime. - Markus Eider; Bernhard Sick; Andreas Berl (Sustain. Comput. Informatics Syst., 2023)

Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories. - Viktor Kress; Fabian Jeske; Stefan Zernetsch; Konrad Doll; Bernhard Sick (IEEE Trans. Intell. Veh., 2023)

Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions. - Chandana Priya Nivarthi; Stephan Vogt; Bernhard Sick (Mach. Learn. Knowl. Extr., 2023)

The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset. - Manuel Hetzel; Hannes Reichert; Günther Reitberger; Konrad Doll; Bernhard Sick (Zenodo, 2023)

Self-Aware Control for Autonomous Underwater Vehicles. - Jens Decke; Florian Gerland; Thomas Schomberg; Olaf Wünsch; Bernhard Sick; Christian Gruhl (ACSOS-C, 2024)

An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing. - Jens Decke; Arne Jenß; Bernhard Sick; Christian Gruhl (ARCS, 2024)

From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in Solving Mesh-Based PDEs. - Jens Decke; Olaf Wünsch; Bernhard Sick; Christian Gruhl (ARCS, 2024)

Sensor Equivariance: A Framework for Semantic Segmentation with Diverse Camera Models. - Hannes Reichert; Manuel Hetzel; Andreas Hubert; Konrad Doll; Bernhard Sick (CVPR Workshops, 2024)

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. - Marek Herde; Lukas Lührs; Denis Huseljic; Bernhard Sick (ECAI, 2024)

Reliable Probabilistic Human Trajectory Prediction for Autonomous Applications. - Manuel Hetzel; Hannes Reichert; Konrad Doll; Bernhard Sick (ECCV Workshops (17), 2024)

Active Learning with Physics-Informed Graph Neural Networks on Unstructured Meshes. - Jens Decke; Alexander Heinen; Bernhard Sick; Christian Gruhl (IAL@PKDD/ECML, 2024)

General Reusability: Ensuring Long-Term Benefits of Deep Active Learning. - Paul Hahn; Denis Huseljic; Marek Herde; Bernhard Sick (IAL@PKDD/ECML, 2024)

Tutorial: Interactive Adaptive Learning. - Marek Herde; Tuan Pham Minh; Alaa Tharwat; Bernhard Sick (IAL@PKDD/ECML, 2024)

Towards Deep Active Learning in Avian Bioacoustics. - Lukas Rauch; Denis Huseljic; Moritz Wirth; Jens Decke; Bernhard Sick; Christoph Scholz 001 (IAL@PKDD/ECML, 2024)

Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Bernhard Sick; Christian Gruhl (ICPR (27), 2024)

Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Christian Gruhl; Bernhard Sick (IJCNN, 2024)

Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. - Chandana Priya Nivarthi; Zhixin Huang; Christian Gruhl; Bernhard Sick (IJCNN, 2024)

Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems. - Martin Braun 002; Christian Gruhl; Christian A. Hans; Philipp Härtel; Christoph Scholz 001; Bernhard Sick; Malte Siefert; Florian Steinke; Olaf Stursberg; Sebastian Wende-von Berg (ISGT EUROPE, 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (NeurIPS, 2024)

Enhancing Multi-objective Optimisation Through Machine Learning-Supported Multiphysics Simulation. - Diego Botache; Jens Decke; Winfried Ripken; Abhinay Dornipati; Franz Götz-Hahn; Mohamed Ayeb; Bernhard Sick (ECML/PKDD (10), 2024)

Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification. - Denis Huseljic; Paul Hahn; Marek Herde; Lukas Rauch; Bernhard Sick (ECML/PKDD (7), 2024)

Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Bernhard Sick (CoRR, 2024)

BirdSet: A Multi-Task Benchmark for Classification in Avian Bioacoustics. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; René Heinrich; Jonas Lange; Stefan Kahl; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (CoRR, 2024)

AudioProtoPNet: An interpretable deep learning model for bird sound classification. - René Heinrich; Bernhard Sick; Christoph Scholz 001 (CoRR, 2024)

Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation. - Florian Heidecker; Ahmad El-Khateeb; Maarten Bieshaar; Bernhard Sick (CoRR, 2024)

Graph Reinforcement Learning in Power Grids: A Survey. - Mohamed Hassouna; Clara Holzhüter; Pawel Lytaev; Josephine M. Thomas; Bernhard Sick; Christoph Scholz 001 (CoRR, 2024)

Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network. - Mohammad Wazed Ali; Asif bin Mustafa; Md. Aukerul Moin Shuvo; Bernhard Sick (CoRR, 2024)

The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification. - Denis Huseljic; Marek Herde; Yannick Nagel; Lukas Rauch; Paulius Strimaitis; Bernhard Sick (Trans. Mach. Learn. Res., 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (Zenodo, 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (Zenodo, 2024)

Towards Cognitive Situational Awareness in Maritime Traffic Using Federated Evidential Learning. - Shang Gao; Zhixin Huang; Ghassan Al-Falouji; Bernhard Sick; Sven Tomforde (CogSIMA, 2025)

BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; René Heinrich; Denis Huseljic; Marek Herde; Jonas Lange; Stefan Kahl; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (ICLR, 2025)

A Concept for Requirements-Driven Identification and Mitigation of Dataset Gaps for Perception Tasks in Automated Driving. - Mohamed Sabry Moustafa; Maarten Bieshaar; Andreas Albrecht; Bernhard Sick (ICPRAM, 2025)

AudioProtoPNet: An interpretable deep learning model for bird sound classification. - René Heinrich; Lukas Rauch; Bernhard Sick; Christoph Scholz 001 (Ecol. Informatics, 2025)

Can Masked Autoencoders Also Listen to Birds? - Lukas Rauch; René Heinrich; Ilyass Moummad; Alexis Joly; Bernhard Sick; Christoph Scholz 001 (Trans. Mach. Learn. Res., 2025)

CARLA Equirectangular Dataset. - Hannes Reichert; Manuel Hetzel; Andreas Hubert; Konrad Doll; Bernhard Sick (Zenodo, 2025)

SemanticTHAB: A High Resolution LiDAR Dataset. - Hannes Reichert; Elijah Schüssler; Benjamin Serfling; Kerim Turacan; Konrad Doll; Bernhard Sick (Zenodo, 2025)

SemanticTHAB: A High Resolution LiDAR Dataset. - Hannes Reichert; Elijah Schüssler; Benjamin Serfling; Kerim Turacan; Konrad Doll; Bernhard Sick (Zenodo, 2025)

Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach. - Mohamed Hassouna; Clara Holzhüter; Malte Lehna; Matthijs de Jong; Jan Viebahn; Bernhard Sick; Christoph Scholz 001 (CoRR, 2025)

Systematic Evaluation of Uncertainty Calibration in Pretrained Object Detectors. - Denis Huseljic; Marek Herde; Paul Hahn; Mehmet Muejde; Bernhard Sick (Int. J. Comput. Vis., 2025)

crowd-hpo: Realistic Hyperparameter Optimization and Benchmarking for Learning from Crowds with Noisy Labels. - Marek Herde; Lukas Lührs; Denis Huseljic; Bernhard Sick (CoRR, 2025)

Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scans. - Hannes Reichert; Benjamin Serfling; Elijah Schüssler; Kerim Turacan; Konrad Doll; Bernhard Sick (CoRR, 2025)

No Free Lunch in Active Learning: LLM Embedding Quality Dictates Query Strategy Success. - Lukas Rauch; Moritz Wirth; Denis Huseljic; Marek Herde; Bernhard Sick; Matthias Aßenmacher (CoRR, 2025)

Flow-Attentional Graph Neural Networks. - Pascal Plettenberg; Dominik Köhler; Bernhard Sick; Josephine M. Thomas (CoRR, 2025)

Graph Neural Networks for Automatic Addition of Optimizing Components in Printed Circuit Board Schematics. - Pascal Plettenberg; André Alcalde; Bernhard Sick; Josephine M. Thomas (CoRR, 2025)

Adversarial Training Improves Generalization Under Distribution Shifts in Bioacoustics. - René Heinrich; Lukas Rauch; Bernhard Sick; Christoph Scholz 001 (CoRR, 2025)