- 28
- 7
- 4
- 1
Alexander Gepperth
40
Documents
Researcher identifiers
alexander-gepperth- IdRef : 19465916X
Presentation
**Personal Information**
Family status: married, 2children
Nationality: German
**Experience in academia**
5/2011 – present Tenured professor at „École Nationale Supérieure de Techniques
Avancées“ (Palaiseau, France)
Assignments: Teaching, research, supervision of theses,
organization of the specialization subject „intelligent vehicles“
Research focus: large-scale learning in intelligent vehicles
**Industrial experience**
02/2008 – 5/2011 Premature tenure as „Senior Scientist“ at Honda Research
Institute Europe GmbH
10/2006 – 2/2008 Four-year contract as „Senior Scientist“ at Honda Research
Institute Europe GmbH, Offenbach am Main, Germany
Assignments: Basic research in machine learning for intelligent
vehicles, implementation of prototypes and demonstrations,
communication to management and academic community,
supervision of students
**PhD thesis**
11/2002 – 04/2006 at the university of Bochum, institute for neural computation
Subject: „Neural learning methods for visual object recognition“
Degree: Dr. rer. nat (grade: „very good“)
Assignments: research, teaching, participation in third-party funded projects (Honda Research Institute Europe GmbH, Robert Bosch KG , DFG Sonderforschungsbereich 475)
**Tertiary education**
10/1996 – 01/2002 Studies in physics at Ludwig-Maximilians-Universität Munich
Diploma thesis: „Non-BPS states in string theory” (grade: 1,7)
Degree: diploma (grade: „very good“)
**Alternate civil service (instead of army service)**
8/1995 - 10/1996 at the municipal hospital Pfaffenhofen/Ilm
**Secondary education**
6/1995 at Schyren-Gymnasium Pfaffenhofen/Ilm, grade: 1,8
**Skills**
Computers Programming: C/C++, CUDA, Python, Matlab
Web programming: HTML, CSS, PHP
Operating systems: Windows, Linux
Real-time middleware: ROS
Scientific standard tools: LaTeX, svn, git, doxygen, bash, eclipse, gnuplot, make, cmake, ...
Libraries: OpenCV, Qt, numpy/scipy, matplotlib/pylab
Languages German, Czech: mother tongues
English, French: fluent
Spanish: advanced level
Japanese:basic level
**Interests**
Tennis, volleyball, bodybuilding, Go, playing the violin, real-time strategy games (Starcraft)
**Personal Information**
Family status: married, 2children
Nationality: German
**Experience in academia**
5/2011 – present Tenured professor at „École Nationale Supérieure de Techniques
Avancées“ (Palaiseau, France)
Assignments: Teaching, research, supervision of theses,
organization of the specialization subject „intelligent vehicles“
Research focus: large-scale learning in intelligent vehicles
**Industrial experience**
02/2008 – 5/2011 Premature tenure as „Senior Scientist“ at Honda Research
Institute Europe GmbH
10/2006 – 2/2008 Four-year contract as „Senior Scientist“ at Honda Research
Institute Europe GmbH, Offenbach am Main, Germany
Assignments: Basic research in machine learning for intelligent
vehicles, implementation of prototypes and demonstrations,
communication to management and academic community,
supervision of students
**PhD thesis**
11/2002 – 04/2006 at the university of Bochum, institute for neural computation
Subject: „Neural learning methods for visual object recognition“
Degree: Dr. rer. nat (grade: „very good“)
Assignments: research, teaching, participation in third-party funded projects (Honda Research Institute Europe GmbH, Robert Bosch KG , DFG Sonderforschungsbereich 475)
**Tertiary education**
10/1996 – 01/2002 Studies in physics at Ludwig-Maximilians-Universität Munich
Diploma thesis: „Non-BPS states in string theory” (grade: 1,7)
Degree: diploma (grade: „very good“)
**Alternate civil service (instead of army service)**
8/1995 - 10/1996 at the municipal hospital Pfaffenhofen/Ilm
**Secondary education**
6/1995 at Schyren-Gymnasium Pfaffenhofen/Ilm, grade: 1,8
**Skills**
Computers Programming: C/C++, CUDA, Python, Matlab
Web programming: HTML, CSS, PHP
Operating systems: Windows, Linux
Real-time middleware: ROS
Scientific standard tools: LaTeX, svn, git, doxygen, bash, eclipse, gnuplot, make, cmake, ...
Libraries: OpenCV, Qt, numpy/scipy, matplotlib/pylab
Languages German, Czech: mother tongues
English, French: fluent
Spanish: advanced level
Japanese:basic level
**Interests**
Tennis, volleyball, bodybuilding, Go, playing the violin, real-time strategy games (Starcraft)
Publications
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 10
- 8
- 5
- 5
- 4
- 4
- 3
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 3
- 2
- 1
- 1
- 10
- 8
- 14
- 1
- 5
- 1
Marginal Replay vs Conditional Replay for Continual LearningICANN, 2019, Munich, Germany
Conference papers
hal-02285835v1
|
|
|
|
Incremental learning algorithms and applicationsEuropean Symposium on Artificial Neural Networks (ESANN), 2016, Bruges, Belgium
Conference papers
hal-01418129v1
|
|
|
Incremental Learning for Bootstrapping Object Classifier ModelsIEEE International Conference On Intelligent Transportation Systems (ITSC), 2016, Seoul, South Korea
Conference papers
hal-01418160v1
|
|
|
Learning to be attractive: probabilistic computation with dynamic attractor networksInternal Conference on Development and LEarning (ICDL), 2016, Cergy-Pontoise, France
Conference papers
hal-01418141v1
|
|
|
Towards incremental deep learning: multi-level change detection in a hierarchical recognition architectureEuropean Symposium on Artificial Neural Networks (ESANN), 2016, Bruges, Belgium
Conference papers
hal-01418132v1
|
|
|
A Deep Learning Approach for Hand Posture Recognition from Depth DataInternational Conference on Artificial Neural Networks (ICANN), 2016, Barcelona, Spain. pp.179 - 186, ⟨10.1007/978-3-319-44781-0_22⟩
Conference papers
hal-01418137v1
|
|
|
Computational Advantages of Deep Prototype-Based LearningInternational Conference on Artificial Neural Networks (ICANN), 2016, Barcelona, Spain. pp.121 - 127, ⟨10.1007/978-3-319-44781-0_15⟩
Conference papers
hal-01418135v1
|
|
|
A simple technique for improving multi-class classification with neural networksEuropean Symposium on artificial neural networks (ESANN), Jun 2015, Bruges, Belgium
Conference papers
hal-01251009v1
|
|
|
Resource-efficient incremental learning in very high dimensionsEuropean Symposium on Artificial Neural Networks (ESANN), Apr 2015, Bruges, Belgium
Conference papers
hal-01251015v1
|
|
|
A generative-discriminative learning model for noisy information fusionInternational Conference on Development and Learning (ICDL), Aug 2015, Providence, United States. ⟨10.1109/DEVLRN.2015.7346148⟩
Conference papers
hal-01250967v1
|
|
|
Biologically inspired incremental learning for high-dimensional spacesJoint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Sep 2015, Providence, United States. ⟨10.1109/DEVLRN.2015.7346155⟩
Conference papers
hal-01250961v1
|
|
|
Using self-organizing maps for regression: the importance of the output functionEuropean Symposium on Artificial Neural Networks (ESANN), Apr 2015, Bruges, Belgium
Conference papers
hal-01251011v1
|
|
|
Learning of local predictable representations in partially learnable environmentsThe International Joint Conference on Neural Networks (IJCNN), Jul 2015, Killarney, Ireland
Conference papers
hal-01205611v1
|
|
|
A light-weight real-time applicable hand gesture recognition system for automotive applicationsIEEE International Symposium on Intelligent Vehicles (IV), Jun 2015, Seoul, South Korea. pp.336-342, ⟨10.1109/IVS.2015.7225708⟩
Conference papers
hal-01251413v1
|
|
|
Active learning of local predictable representations with artificial curiosityInternational Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob), Aug 2015, Providence, United States
Conference papers
hal-01205619v1
|
|
|
Context-based vector fields for multi-object tracking in application to road trafficIEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.1179 - 1185, ⟨10.1109/ITSC.2014.6957847⟩
Conference papers
hal-01098701v2
|
|
|
Latency-Based Probabilistic Information Processing in Recurrent Neural HierarchiesInternational Conference on Artificial Neural Networks (ICANN), Sep 2014, Hamburg, Germany. pp.715 - 722, ⟨10.1007/978-3-319-11179-7_90⟩
Conference papers
hal-01098699v1
|
|
|
Scene context is more than a Bayesian prior: Competitive vehicle detection with restricted detectorsIEEE International Symposium on Intelligent Vehicles(IV), May 2014, Detroit, United States. pp.1358 - 1364, ⟨10.1109/IVS.2014.6856542⟩
Conference papers
hal-01098707v1
|
|
|
A real-time applicable 3D gesture recognition system for automobile HMIIEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.2616 - 2622, ⟨10.1109/ITSC.2014.6958109⟩
Conference papers
hal-01098700v1
|
|
|
A Multi-Modal System for Road Detection and SegmentationIEEE Intelligent Vehicles Symposium, Jun 2014, Dearborn, Michigan, United States. pp.1365-1370
Conference papers
hal-01023615v1
|
|
|
Discrimination of visual pedestrians data by combining projection and prediction learningEuropean Symposium on artificial neural networks (ESANN), Apr 2014, Bruges, Belgium
Conference papers
hal-01061654v1
|
|
|
Multimodal space representation driven by self-evaluation of predictabilityJoint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Oct 2014, Gênes, Italy
Conference papers
hal-01061668v1
|
|
|
Neural Network Fusion of Color, Depth and Location for Object Instance Recognition on a Mobile RobotSecond Workshop on Assistive Computer Vision and Robotics (ACVR), in conjunction with European Conference on Computer Vision, Sep 2014, Zurich, Switzerland
Conference papers
hal-01087392v1
|
|
|
Time-of-Flight based multi-sensor fusion strategies for hand gesture recognitionIEEE International Symposium on Computational Intelligence and Informatics, Nov 2014, Budapest, Hungary
Conference papers
hal-01098695v1
|
|
|
Latency-based probabilistic information processing in a learning feedback hierarchyInternational Joint Conference on Neural Networks (IJCNN), Jun 2014, Beijing, China. pp.3031 - 3037, ⟨10.1109/IJCNN.2014.6889919⟩
Conference papers
hal-01098704v1
|
|
|
Robust visual pedestrian detection by tight coupling to trackingIEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.1935 - 1940, ⟨10.1109/ITSC.2014.6957989⟩
Conference papers
hal-01098703v1
|
|
|
Neural network based 2D/3D fusion for robotic object recognitionEuropean Symposium on artificial neural networks (ESANN), May 2014, Bruges, Belgium. pp.127 - 132
Conference papers
hal-01012090v1
|
|
|
Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF SensorsInternational Conference on Artificial Neural Networks (ICANN), Sep 2014, Hamburg, Germany. pp.233 - 240, ⟨10.1007/978-3-319-11179-7_30⟩
Conference papers
hal-01098697v1
|
|
|
PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discriminationIJCNN - International Joint Conference on Neural Networks, Jul 2014, Pékin, China
Conference papers
hal-01061662v1
|
|
|
A Comparison of Geometric and Energy-Based Point Cloud Semantic Segmentation Methods6th European Conference on Mobile Robotics (ECMR), IEEE, Sep 2013, Barcelona, Spain. pp.88-93, ⟨10.1109/ECMR.2013.6698825⟩
Conference papers
hal-00963863v1
|
|
|
Simultaneous concept formation driven by predictabilityInternational conference on development and learning, Nov 2012, San Diego, United States
Conference papers
hal-00763671v1
|
|
|
Co-training of context models for real-time object detectionIEEE Symposium on Intelligent Vehicles, Jun 2012, Madrid, Spain
Conference papers
hal-00763676v1
|
|
|
RGBD object recognition and visual texture classification for indoor semantic mappingTechnologies for Practical Robot Applications (TePRA), 2012 IEEE International Conference on, Apr 2012, United States. pp.127 - 132, ⟨10.1109/TePRA.2012.6215666⟩
Conference papers
hal-00755295v1
|
|
|
New learning paradigms for real-world environment perceptionMachine Learning [cs.LG]. Université Pierre & Marie Curie, 2016
Accreditation to supervise research
tel-01418147v1
|