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ORCIDBernhard Sick
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- affiliation: University of Kassel, Germany
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2020 – today
- 2021
[j42]Kristina Dingel
, Rico Huhnstock, André Knie, Arno Ehresmann, Bernhard Sick:
AdaPT: Adaptable Particle Tracking for spherical microparticles in lab on chip systems. Comput. Phys. Commun. 262: 107859 (2021)- [j41]Christian Gruhl, Bernhard Sick, Sven Tomforde:
Novelty detection in continuously changing environments. Future Gener. Comput. Syst. 114: 138-154 (2021) - [j40]Sarah Oeste-Reiß, Eva A. C. Bittner, Izabel Cvetkovic, Andreas Günther, Jan Marco Leimeister, Lucas Memmert, Anja Ott, Bernhard Sick, Kathrin Wolter:
Hybride Wissensarbeit. Inform. Spektrum 44(3): 148-152 (2021) - [j39]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward optimal probabilistic active learning using a Bayesian approach. Mach. Learn. 110(6): 1199-1231 (2021) - [i42]Yujiang He, Bernhard Sick:
CLeaR: An Adaptive Continual Learning Framework for Regression Tasks. CoRR abs/2101.00926 (2021) - [i41]Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick:
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving. CoRR abs/2103.03678 (2021) - [i40]Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick:
Cyclist Intention Detection: A Probabilistic Approach. CoRR abs/2104.09176 (2021) - [i39]Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick:
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders. CoRR abs/2105.02965 (2021) - [i38]Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Bernhard Sick, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner:
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. CoRR abs/2105.06896 (2021) - [i37]Viktor Kress, Fabian Jeske, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories. CoRR abs/2106.02598 (2021) - [i36]Stefan Zernetsch, Oliver Trupp, Viktor Kress, Konrad Doll, Bernhard Sick:
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information. CoRR abs/2106.15991 (2021) - 2020
- [j38]Michael Goldhammer, Sebastian Köhler, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Klaus Dietmayer:
Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning. IEEE Trans. Intell. Transp. Syst. 21(7): 3035-3045 (2020) - [c122]Christian Gruhl, Jörn Schmeißing, Sven Tomforde, Bernhard Sick:
Normal-Wishart Clustering for Novelty Detection. ACSOS Companion 2020: 64-69 - [c121]Sven Tomforde, Christian Gruhl, Bernhard Sick:
A Swarm-fleet Infrastructure as a Scenario for Proactive, Hybrid Adaptation of System Behaviour. ACSOS Companion 2020: 166-169 - [c120]Nicolas Scheiner, Florian Kraus, Fangyin Wei, Buu Phan, Fahim Mannan, Nils Appenrodt, Werner Ritter, Jürgen Dickmann, Klaus Dietmayer, Bernhard Sick, Felix Heide:
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar. CVPR 2020: 2065-2074 - [c119]Nicolas Scheiner, Ole Schumann, Florian Kraus, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification? FUSION 2020: 1-8 - [c118]Viktor Kress, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Trajectory Forecast of Vulnerable Road Users Using Recurrent Neural Networks. ICPR Workshops (1) 2020: 57-71 - [c117]Florian Heidecker, Abdul Hannan, Maarten Bieshaar, Bernhard Sick:
Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. ICPR Workshops (4) 2020: 361-374 - [c116]Jan Schneegans, Maarten Bieshaar, Florian Heidecker, Bernhard Sick:
Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. ICPR Workshops (4) 2020: 375-389 - [c115]Florian Heidecker, Christian Gruhl, Bernhard Sick:
Novelty Based Driver Identification on RR Intervals from ECG Data. ICPR Workshops (4) 2020: 407-421 - [c114]Stefan Zernetsch, Steven Schreck, Viktor Kress, Konrad Doll, Bernhard Sick:
Image Sequence Based Cyclist Action Recognition Using Multi-Stream 3D Convolution. ICPR 2020: 2620-2626 - [c113]Jens Schreiber, Bernhard Sick:
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems. ICPR 2020: 2663-2670 - [c112]Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke:
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. ICPR 2020: 9172-9179 - [c111]Christian Haase-Schütz, Rainer Stal, Heinz Hertlein, Bernhard Sick:
Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning. ICPR 2020: 9483-9490 - [c110]Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick:
Multi-Annotator Probabilistic Active Learning. ICPR 2020: 10281-10288 - [c109]Yujiang He, Janosch Henze, Bernhard Sick:
Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks. IJCNN 2020: 1-8 - [c108]Tuan Pham Minh, Daniel Kottke, Anna Tsarenko, Christian Gruhl, Bernhard Sick:
Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. IJCNN 2020: 1-8 - [c107]Viktor Kress, Steven Schreck, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Action Recognition of Vulnerable Road Users Using Recurrent Neural Networks. SSCI 2020: 2723-2730 - [i35]Christian Haase-Schütz, Rainer Stal, Heinz Hertlein, Bernhard Sick:
Trust Your Model: Iterative Label Improvement and Robust Training by Confidence Based Filtering and Dataset Partitioning. CoRR abs/2002.02705 (2020) - [i34]Stephan Deist, Jens Schreiber, Maarten Bieshaar, Bernhard Sick:
Extended Coopetitive Soft Gating Ensemble. CoRR abs/2004.14026 (2020) - [i33]Jens Schreiber, Bernhard Sick:
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems. CoRR abs/2004.14034 (2020) - [i32]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR abs/2006.01732 (2020) - [i31]Nicolas Scheiner, Ole Schumann, Florian Kraus, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification? CoRR abs/2006.05485 (2020) - [i30]Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm:
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR abs/2009.13853 (2020) - [i29]Maarten Bieshaar, Jens Schreiber, Stephan Vogt, André Gensler, Bernhard Sick:
Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets. CoRR abs/2010.05898 (2020)
2010 – 2019
- 2019
- [c106]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Start Intention Detection of Cyclists using an LSTM Network. GI-Jahrestagung (Workshops) 2019: 219-228 - [c105]Diego Botache, Dandan Liu, Maarten Bieshaar, Bernhard Sick:
Early Pedestrian Movement Detection Using Smart Devices Based on Human Activity Recognition. GI-Jahrestagung (Workshops) 2019: 229-238 - [c104]Immanuel König, Erik Heilmann, Janosch Henze, Klaus David, Heike Wetzel, Bernhard Sick:
Using grid supporting flexibility in electricity distribution networks. GI-Jahrestagung 2019: 531-544 - [c103]Jens Schreiber, Artjom Buschin, Bernhard Sick:
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. GI-Jahrestagung 2019: 585-598 - [c102]Jens Schreiber, Maik Jessulat, Bernhard Sick:
Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. ICANN (3) 2019: 550-564 - [c101]Christoph Sandrock, Marek Herde, Adrian Calma, Daniel Kottke, Bernhard Sick:
Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. IJCNN 2019: 1-8 - [c100]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
A Multi-Stage Clustering Framework for Automotive Radar Data. ITSC 2019: 2060-2067 - [c99]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Start Intention Detection of Cyclists. ITSC 2019: 2381-2386 - [c98]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles. IV 2019: 722-729 - [c97]Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick:
Trajectory Forecasts with Uncertainties of Vulnerable Road Users by Means of Neural Networks. IV 2019: 810-815 - [c96]Viktor Kress, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Trajectory Forecast of Vulnerable Road Users. SSCI 2019: 1200-1207 - [e5]Claude Draude, Martin Lange, Bernhard Sick:
49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft, INFORMATIK 2019 - Workshops, Kassel, Germany, September 23-26, 2019. LNI P-295, GI 2019, ISBN 978-3-88579-689-3 [contents] - [i28]Daniel Kottke, Jim Schellinger, Denis Huseljic, Bernhard Sick:
Limitations of Assessing Active Learning Performance at Runtime. CoRR abs/1901.10338 (2019) - [i27]Tom Hanika, Marek Herde, Jochen Kuhn, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiß, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. CoRR abs/1905.07264 (2019) - [i26]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS. CoRR abs/1905.11219 (2019) - [i25]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Feature Design and Multiclass Classification for Road User Recognition. CoRR abs/1905.11256 (2019) - [i24]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles. CoRR abs/1905.11703 (2019) - [i23]Nicolas Scheiner, Stefan Haag, Nils Appenrodt, Bharanidhar Duraisamy, Jürgen Dickmann, Martin Fritzsche, Bernhard Sick:
Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices. CoRR abs/1905.11987 (2019) - [i22]Jens Schreiber, Artjom Buschin, Bernhard Sick:
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. CoRR abs/1905.13668 (2019) - [i21]Jens Schreiber, Maik Jessulat, Bernhard Sick:
Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. CoRR abs/1906.00662 (2019) - [i20]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
A Multi-Stage Clustering Framework for Automotive Radar Data. CoRR abs/1907.03511 (2019) - [i19]Nicolas Scheiner, Florian Kraus, Fangyin Wei, Buu Phan, Fahim Mannan, Nils Appenrodt, Werner Ritter, Jürgen Dickmann, Klaus Dietmayer, Bernhard Sick, Felix Heide:
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar. CoRR abs/1912.06613 (2019) - 2018
- [j37]Sebastian Breker, Jan Rentmeister, Bernhard Sick, Martin Braun:
Hosting capacity of low-voltage grids for distributed generation: Classification by means of machine learning techniques. Appl. Soft Comput. 70: 195-207 (2018) - [j36]Martin Jänicke, Bernhard Sick, Sven Tomforde:
Self-Adaptive Multi-Sensor Activity Recognition Systems Based on Gaussian Mixture Models. Informatics 5(3): 38 (2018) - [j35]Bernhard Sick, Sarah Oeste-Reiß, Albrecht Schmidt, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning. Inform. Spektrum 41(1): 52-55 (2018) - [j34]Adrian Calma, Tobias Reitmaier, Bernhard Sick:
Semi-supervised active learning for support vector machines: A novel approach that exploits structure information in data. Inf. Sci. 456: 13-33 (2018) - [j33]Christian Gruhl, Bernhard Sick:
Novelty detection with CANDIES: a holistic technique based on probabilistic models. Int. J. Mach. Learn. Cybern. 9(6): 927-945 (2018) - [j32]Andre Gensler, Bernhard Sick:
Performing event detection in time series with SwiftEvent: an algorithm with supervised learning of detection criteria. Pattern Anal. Appl. 21(2): 543-562 (2018) - [j31]Sven Tomforde, Jan Kantert, Christian Müller-Schloer, Sebastian Bödelt, Bernhard Sick:
Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness. Trans. Comput. Collect. Intell. 28: 193-220 (2018) - [j30]Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert, Bernhard Sick, Konrad Doll:
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble. IEEE Trans. Intell. Veh. 3(4): 534-544 (2018) - [c95]Maarten Bieshaar, Malte Depping, Jan Schneegans, Bernhard Sick:
Starting Movement Detection of Cyclists Using Smart Devices. DSAA 2018: 313-322 - [c94]Adrian Calma, Sarah Oeste-Reiß, Bernhard Sick, Jan Marco Leimeister:
Leveraging the Potentials of Dedicated Collaborative Interactive Learning: Conceptual Foundations to Overcome Uncertainty by Human-Machine Collaboration. HICSS 2018: 1-9 - [c93]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz:
Hijacked Smart Devices - Methodical Foundations for Autonomous Theft Awareness based on Activity Recognition and Novelty Detection. ICAART (2) 2018: 131-142 - [c92]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz, Jörn Schmeißing:
Smart Device Stealing and CANDIES. ICAART (Revised Selected Papers) 2018: 247-273 - [c91]Adrian Calma, Moritz Stolz, Daniel Kottke, Sven Tomforde, Bernhard Sick:
Active Learning With Realistic Data - A Case Study. IJCNN 2018: 1-8 - [c90]Marek Herde, Daniel Kottke, Adrian Calma, Maarten Bieshaar, Stephan Deist, Bernhard Sick:
Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. IJCNN 2018: 1-8 - [c89]Daniel Kottke, Adrian Calma, Denis Huseljic, Christoph Sandrock, George Kachergis, Bernhard Sick:
The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning. IJCNN 2018: 1-8 - [c88]Günther Reitberger, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Erich Fuchs:
Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. ITSC 2018: 436-443 - [c87]Stefan Zernetsch, Viktor Kress, Bernhard Sick, Konrad Doll:
Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network. Intelligent Vehicles Symposium 2018: 1-6 - [c86]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Feature Design and Multiclass Classification for Road User Recognition. Intelligent Vehicles Symposium 2018: 779-786 - [c85]Andreas Jahn, Sven Tomforde, Michel Morold, Klaus David, Bernhard Sick:
Towards Cooperative Self-adapting Activity Recognition. PECCS 2018: 215-222 - [c84]Janosch Henze, Stephan Kutzner, Bernhard Sick:
Sampling Strategies for Representative Time Series in Load Flow Calculations. DARE@PKDD/ECML 2018: 27-48 - [c83]Henner Heck, Bernhard Sick, Sven Tomforde:
Security Issues in Self-Improving System Integration - Challenges and Solution Strategies. FAS*W@SASO/ICAC 2018: 176-181 - [c82]Jens Schreiber, Maarten Bieshaar, Andre Gensler, Bernhard Sick, Stephan Deist:
Coopetitive Soft Gating Ensemble. FAS*W@SASO/ICAC 2018: 190-197 - [c81]Christian Gruhl, Sven Tomforde, Bernhard Sick:
Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. FAS*W@SASO/ICAC 2018: 198-203 - [c80]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Human Pose Estimation in Real Traffic Scenes. SSCI 2018: 518-523 - [e4]Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. CEUR Workshop Proceedings 2192, CEUR-WS.org 2018 [contents] - [i18]Günther Reitberger, Stefan Zernetsch, Maarten Bieshaar, Bernhard Sick, Konrad Doll, Erich Fuchs:
Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. CoRR abs/1803.02096 (2018) - [i17]Stefan Zernetsch, Viktor Kress, Bernhard Sick, Konrad Doll:
Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network. CoRR abs/1803.02242 (2018) - [i16]Maarten Bieshaar, Günther Reitberger, Viktor Kreß, Stefan Zernetsch, Konrad Doll, Erich Fuchs, Bernhard Sick:
Highly Automated Learning for Improved Active Safety of Vulnerable Road Users. CoRR abs/1803.03479 (2018) - [i15]Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert, Bernhard Sick, Konrad Doll:
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble. CoRR abs/1803.03487 (2018) - [i14]Michael Goldhammer, Sebastian Köhler, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Klaus Dietmayer:
Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning. CoRR abs/1803.03577 (2018) - [i13]Stephan Deist, Maarten Bieshaar, Jens Schreiber, Andre Gensler, Bernhard Sick:
Coopetitive Soft Gating Ensemble. CoRR abs/1807.01020 (2018) - [i12]Maarten Bieshaar, Malte Depping, Jan Schneegans, Bernhard Sick:
Starting Movement Detection of Cyclists Using Smart Devices. CoRR abs/1808.04449 (2018) - [i11]Jens Schreiber, Bernhard Sick:
Quantifying the Influences on Probabilistic Wind Power Forecasts. CoRR abs/1808.04750 (2018) - [i10]Maarten Bieshaar, Günther Reitberger, Stefan Zernetsch, Bernhard Sick, Erich Fuchs, Konrad Doll:
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence. CoRR abs/1809.03916 (2018) - 2017
- [c79]Jan Kantert, Sven Tomforde, Christian Müller-Schloer, Sarah Edenhofer, Bernhard Sick:
Quantitative Robustness - A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems. ICAART (1) 2017: 39-50 - [c78]Sven Tomforde, Jan Kantert, Bernhard Sick:
Measuring Self-organisation at Runtime - A Quantification Method based on Divergence Measures. ICAART (1) 2017: 96-106 - [c77]Bernhard Schlegel, Bernhard Sick:
Dealing with Class Imbalance the Scalable Way: Evaluation of Various Techniques Based on Classification Grade and Computational Complexity. ICDM Workshops 2017: 69-78 - [c76]Klaus-Hendrik Wolf, Tobias Dehling, Reinhold Haux, Bernhard Sick, Ali Sunyaev, Sven Tomforde:
On Methodological and Technological Challenges for Proactive Health Management in Smart Homes. ICIMTH 2017: 209-212 - [c75]Maarten Bieshaar, Stefan Zernetsch, Malte Depping, Bernhard Sick, Konrad Doll:
Cooperative starting intention detection of cyclists based on smart devices and infrastructure. ITSC 2017: 1-8 - [c74]Andreas Hubert, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Cyclists' starting behavior at intersections. Intelligent Vehicles Symposium 2017: 1071-1077 - [c73]Daniel Kottke, Adrian Calma, Denis Huseljic, Georg Krempl, Bernhard Sick:
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. IAL@PKDD/ECML 2017: 2-14 - [c72]Adrian Calma, Bernhard Sick:
Simulation of Annotators for Active Learning: Uncertain Oracles. IAL@PKDD/ECML 2017: 49-58 - [c71]Janosch Henze, Tanja Kneiske, Martin Braun, Bernhard Sick:
Identifying Representative Load Time Series for Load Flow Calculations. DARE@PKDD/ECML 2017: 83-93 - [c70]Adrian Calma, Daniel Kottke, Bernhard Sick, Sven Tomforde:
Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms. FAS*W@SASO/ICCAC 2017: 109-116 - [c69]Jan Eilbrecht, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Olaf Stursberg:
Model-predictive planning for autonomous vehicles anticipating intentions of vulnerable road users by artificial neural networks. SSCI 2017: 1-8 - [c68]Andre Gensler, Bernhard Sick:
Probabilistic wind power forecasting: A multi-scheme ensemble technique with gradual coopetitive soft gating. SSCI 2017: 1-10 - [e3]Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma:
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1924, CEUR-WS.org 2017 [contents] - [i9]Sven Tomforde, Bernhard Sick, Christian Müller-Schloer:
Organic Computing in the Spotlight. CoRR abs/1701.08125 (2017) - [i8]David Bannach, Martin Jänicke, Vitor F. Rey, Sven Tomforde, Bernhard Sick, Paul Lukowicz:
Self-Adaptation of Activity Recognition Systems to New Sensors. CoRR abs/1701.08528 (2017) - 2016
- [j29]Dominik Fisch, Christian Gruhl, Edgar Kalkowski, Bernhard Sick, Seppo J. Ovaska:
Towards automation of knowledge understanding: An approach for probabilistic generative classifiers. Inf. Sci. 370-371: 476-496 (2016) - [c67]Gerald Pirkl, Peter Hevesi, Paul Lukowicz, Pascal Klein, Carina Heisel, Sebastian Gröber, Jochen Kuhn, Bernhard Sick:
Any problems? a wearable sensor-based platform for representational learning-analytics. UbiComp Adjunct 2016: 353-356 - [c66]Martin Jänicke, Sven Tomforde, Bernhard Sick:
Towards Self-Improving Activity Recognition Systems Based on Probabilistic, Generative Models. ICAC 2016: 285-291 - [c65]Gernot Bahle, Adrian Calma, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiss, Tobias Reitmaier, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Katharina Anna Zweig:
Lifelong Learning and Collaboration of Smart Technical Systems in Open-Ended Environments - Opportunistic Collaborative Interactive Learning. ICAC 2016: 315-324 - [c64]Edgar Kalkowski, Bernhard Sick:
Correlation of Ontology-Based Semantic Similarity and Human Judgement for a Domain Specific Fashion Ontology. ICWE 2016: 207-224 - [c63]Sebastian Breker, Bernhard Sick:
Combination of uncertain ordinal expert statements: The combination rule EIDMR and its application to low-voltage grid classification with SVM. IJCNN 2016: 2164-2173 - [c62]Adrian Calma, Tobias Reitmaier, Bernhard Sick:
Resp-kNN: A probabilistic k-nearest neighbor classifier for sparsely labeled data. IJCNN 2016: 4040-4047 - [c61]Andre Gensler, Bernhard Sick:
Forecasting wind power - an ensemble technique with gradual coopetitive weighting based on weather situation. IJCNN 2016: 4976-4984 - [c60]Stefan Zernetsch, Sascha Kohnen, Michael Goldhammer, Konrad Doll, Bernhard Sick:
Trajectory prediction of cyclists using a physical model and an artificial neural network. Intelligent Vehicles Symposium 2016: 833-838 - [c59]Matthias Kreil, Bernhard Sick, Paul Lukowicz:
Coping with variability in motion based activity recognition. iWOAR 2016: 4:1-4:8 - [c58]Henner Heck, Stefan Rudolph, Christian Gruhl, Arno Wacker, Jörg Hähner, Bernhard Sick, Sven Tomforde:
Towards Autonomous Self-Tests at Runtime. FAS*W@SASO/ICCAC 2016: 98-99 - [c57]Andre Gensler, Bernhard Sick, Vitali Pankraz:
An analog ensemble-based similarity search technique for solar power forecasting. SMC 2016: 2850-2857 - [c56]Andre Gensler, Janosch Henze, Bernhard Sick, Nils Raabe:
Deep Learning for solar power forecasting - An approach using AutoEncoder and LSTM Neural Networks. SMC 2016: 2858-2865 - [c55]Andre Gensler, Bernhard Sick, Stephan Vogt:
A review of deterministic error scores and normalization techniques for power forecasting algorithms. SSCI 2016: 1-9 - [c54]