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ORCIDJochen Hipp
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2020 – today
- 2025
[i9]Christian Reichenbächer, Philipp Rank, Jochen Hipp, Oliver Bringmann:
Estimating the Joint Probability of Scenario Parameters with Gaussian Mixture Copula Models. CoRR abs/2506.10098 (2025)- 2024
- [i8]Christian Reichenbächer, Jochen Hipp, Oliver Bringmann:
Statistical Modelling of Driving Scenarios in Road Traffic using Fleet Data of Production Vehicles. CoRR abs/2404.06288 (2024) - 2022
- [c18]Christian Reichenbächer, Maximilian Rasch, Zafer Kayatas
, Florian Wirthmüller, Jochen Hipp, Thao Dang, Oliver Bringmann:
Identifying Scenarios in Field Data to Enable Validation of Highly Automated Driving Systems. VEHITS 2022: 134-142 - [i7]Christian Reichenbächer, Maximilian Rasch, Zafer Kayatas, Florian Wirthmüller, Jochen Hipp, Thao Dang, Oliver Bringmann:
Identifying Scenarios in Field Data to Enable Validation of Highly Automated Driving Systems. CoRR abs/2203.03515 (2022) - 2021
- [j8]Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Predicting the Time Until a Vehicle Changes the Lane Using LSTM-Based Recurrent Neural Networks. IEEE Robotics Autom. Lett. 6(2): 2357-2364 (2021) - [j7]Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction Using Large Data Sets. IEEE Trans. Intell. Transp. Syst. 22(11): 7129-7144 (2021) - [c17]Florian Wirthmüller, Jochen Hipp, Christian Reichenbächer, Manfred Reichert:
The Atlas of Lane Changes: Investigating Location-Dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet. ITSC 2021: 1225-1232 - [i6]Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Predicting the Time Until a Vehicle Changes the Lane Using LSTM-based Recurrent Neural Networks. CoRR abs/2102.01431 (2021) - [i5]Florian Wirthmüller, Jochen Hipp, Christian Reichenbächer, Manfred Reichert:
The Atlas of Lane Changes: Investigating Location-dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet. CoRR abs/2107.04029 (2021) - 2020
- [c16]Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior. ITSC 2020: 1-7 - [c15]Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
A Fleet Learning Architecture for Enhanced Behavior Predictions during Challenging External Conditions. SSCI 2020: 2739-2745 - [i4]Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior. CoRR abs/2006.08470 (2020) - [i3]Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
A Fleet Learning Architecture for Enhanced Behavior Predictions during Challenging External Conditions. CoRR abs/2009.11221 (2020)
2010 – 2019
- 2019
- [c14]Florian Wirthmueller, Jochen Hipp, Kai-Uwe Sattler, Manfred Reichert:
CPD: Crowd-based Pothole Detection. VEHITS 2019: 33-42 - [i2]Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp, Manfred Reichert:
Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction using Large Data Sets. CoRR abs/1910.07772 (2019) - 2016
- [c13]Kay Massow, Birgit Kwella, Niko Pfeifer, Florian Hausler, Jens Pontow, Ilja Radusch, Jochen Hipp, Frank Dölitzscher, Martin Haueis:
Deriving HD maps for highly automated driving from vehicular probe data. ITSC 2016: 1745-1752 - 2014
- [j6]Julius Ziegler, Philipp Bender, Markus Schreiber, Henning Lategahn, Tobias Strauss, Christoph Stiller, Thao Dang, Uwe Franke, Nils Appenrodt, Christoph Gustav Keller, Eberhard Kaus, Ralf G. Herrtwich, Clemens Rabe, David Pfeiffer, Frank Lindner, Fridtjof Stein, Friedrich Erbs, Markus Enzweiler, Carsten Knöppel, Jochen Hipp, Martin Haueis, Maximilian Trepte, Carsten Brenk, Andreas Tamke, Mohammad Ghanaat, Markus Braun, Armin Joos, Hans Fritz, Horst Mock, Martin Hein, Eberhard Zeeb:
Making Bertha Drive - An Autonomous Journey on a Historic Route. IEEE Intell. Transp. Syst. Mag. 6(2): 8-20 (2014) - [c12]Julius Ziegler, Henning Lategahn, Markus Schreiber, Christoph Gustav Keller, Carsten Knöppel, Jochen Hipp, Martin Haueis, Christoph Stiller:
Video based localization for Bertha. Intelligent Vehicles Symposium 2014: 1231-1238 - 2010
- [p1]Axel Blumenstock, Markus Mueller, Carsten Lanquillon, Steffen Kempe, Jochen Hipp, Rüdiger Wirth:
Interactivity Closes the Gap - Lessons Learned in an Automotive Industry Application. Data Mining for Business Applications 2010: 17-34
2000 – 2009
- 2008
- [j5]Steffen Kempe, Jochen Hipp, Carsten Lanquillon, Rudolf Kruse:
Mining Frequent Temporal Patterns in Interval Sequences. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 16(5): 645-661 (2008) - 2007
- [c11]Steffen Kempe, Jochen Hipp, Rudolf Kruse:
FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns. GfKl 2007: 253-260 - [c10]Jochen Hipp, Markus Müller, Johannes Hohendorff, Felix Naumann:
Rule-Based Measurement Of Data Quality In Nominal Data. ICIQ 2007: 364-378 - 2006
- [c9]Steffen Kempe, Jochen Hipp:
Mining Sequences of Temporal Intervals. PKDD 2006: 569-576 - 2005
- [j4]Joachim Kübart, Udo Grimmer, Jochen Hipp:
Regelbasierte Ausreißersuche zur Datenqualitätsanalyse. Datenbank-Spektrum 14: 22-28 (2005) - 2004
- [c8]Tomas Hrycej, Jochen Hipp:
Outlier Detection by Rareness Assumption. GI Jahrestagung (1) 2004: 244-248 - [i1]Raghu Ramakrishnan, Rakesh Agrawal, Johann-Christoph Freytag, Toni Bollinger, Christopher W. Clifton, Saso Dzeroski, Jochen Hipp, Daniel A. Keim, Stefan Kramer, Hans-Peter Kriegel, Ulf Leser, Bing Liu, Heikki Mannila, Rosa Meo, Shinichi Morishita, Raymond T. Ng, Jian Pei, Prabhakar Raghavan, Myra Spiliopoulou, Jaideep Srivastava, Vicenç Torra:
Data Mining: The Next Generation. Perspectives Workshop: Data Mining: The Next Generation 2004 - 2003
- [b1]Jochen Hipp:
Wissensentdeckung in Datenbanken mit Assoziationsregeln: Verfahren zur effizienten Regelgenerierung und deren Integration in den Wissensentdeckungsprozeß. University of Tübingen, Germany, AKA 2003, ISBN 3-89838-485-3, pp. 1-214 - 2002
- [j3]Jochen Hipp, Ulrich Güntzer:
Is pushing constraints deeply into the mining algorithms really what we want?: an alternative approach for association rule mining. SIGKDD Explor. 4(1): 50-55 (2002) - [c7]Jochen Hipp, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
Data Mining of Association Rules and the Process of Knowledge Discovery in Databases. ICDM 2002: 15-36 - [c6]Jochen Hipp, Christoph Mangold, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining. PAKDD 2002: 52-65 - 2001
- [c5]Jochen Hipp, Ulrich Güntzer, Udo Grimmer:
Data Quality Mining - Making a Virute of Necessity. DMKD 2001 - [c4]Jochen Hipp, Ulrich Güntzer, Udo Grimmer:
Integrating Association Rule Mining Algorithms with Relational Database Systems. ICEIS (1) 2001: 130-137 - 2000
- [j2]Christoph Stiller, Jochen Hipp, C. Rössig, A. Ewald:
Multisensor obstacle detection and tracking. Image Vis. Comput. 18(5): 389-396 (2000) - [j1]Jochen Hipp, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
Algorithms for Association Rule Mining - A General Survey and Comparison. SIGKDD Explor. 2(1): 58-64 (2000) - [c3]Jochen Hipp, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
Mining Association Rules: Deriving a Superior Algorithm by Analyzing Today's Approaches. PKDD 2000: 159-168
1990 – 1999
- 1999
- [c2]Jochen Hipp, Guido Lindner:
Analysing Warranty Claims of Automobiles; An Application Description Following the CRISP-DM Data Mining Process. ICSC 1999: 31-40 - 1998
- [c1]Jochen Hipp, Andreas Myka, Rüdiger Wirth, Ulrich Güntzer:
A New Algorithm for Faster Mining of Generalized Association Rules. PKDD 1998: 74-82
Coauthor Index
aka: Florian Wirthmüller
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