Alexander Gepperth

Identifiants chercheurs

IdHAL :

alexander-gepperth

IdRef :

19465916X

Présentation

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

Article dans une revue (6)

Dynamic attention priors: a new and efficient concept for improving object detection Alexander Gepperth,Michael Garcia Ortiz,Egor Sattarov,Bernd Heisele Neurocomputing, 2016, 197, pp.14 - 28. ⟨10.1016/j.neucom.2016.01.036⟩ Article dans une revue hal-01418128v1
A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems Alexander Gepperth,Cem Karaoguz Cognitive Computation, 2016, 8, pp.924 - 934. ⟨10.1007/s12559-016-9389-5⟩ Article dans une revue hal-01418123v1
A Generative Learning Approach to Sensor Fusion and Change Detection Alexander Gepperth,Thomas Hecht,Mandar Gogate Cognitive Computation, 2016, 8, pp.806 - 817. ⟨10.1007/s12559-016-9390-z⟩ Article dans une revue hal-01418125v1
The contribution of context information: a case study of object recognition in an intelligent car Alexander Gepperth,Benjamin Dittes,Michaël Garcia Ortiz Neurocomputing, 2012, 94, ⟨10.1016/j.neucom.2012.03.008⟩ Article dans une revue hal-00763650v1
Efficient online bootstrapping of sensory representations Alexander Gepperth Neural Networks, 2012, Special Issue on Autonomous Learning, ⟨10.1016/j.neunet.2012.11.002⟩ Article dans une revue hal-00763660v1
Biased competition in visual processing hierarchies: a learning approach using multiple cues Alexander Gepperth,Sven Rebhan,Stephan Hasler,Jannik Fritsch Cognitive Computation, 2011, 3 (1) Article dans une revue hal-00647809v1

Communication dans un congrès (33)

Marginal Replay vs Conditional Replay for Continual Learning Timothée Lesort,Alexander Gepperth,Andrei Stoian,David Filliat ICANN, 2019, Munich, Germany Communication dans un congrès hal-02285835v1
Towards incremental deep learning: multi-level change detection in a hierarchical recognition architecture Thomas Hecht,Alexander Gepperth European Symposium on Artificial Neural Networks (ESANN), 2016, Bruges, Belgium Communication dans un congrès hal-01418132v1
Incremental Learning for Bootstrapping Object Classifier Models Cem Karaoguz,Alexander Gepperth IEEE International Conference On Intelligent Transportation Systems (ITSC), 2016, Seoul, South Korea Communication dans un congrès hal-01418160v1
Incremental learning algorithms and applications Alexander Gepperth,Barbara Hammer European Symposium on Artificial Neural Networks (ESANN), 2016, Bruges, Belgium Communication dans un congrès hal-01418129v1
Learning to be attractive: probabilistic computation with dynamic attractor networks Alexander Gepperth,Mathieu Lefort Internal Conference on Development and LEarning (ICDL), 2016, Cergy-Pontoise, France Communication dans un congrès hal-01418141v1
Computational Advantages of Deep Prototype-Based Learning Thomas Hecht,Alexander Gepperth International Conference on Artificial Neural Networks (ICANN), 2016, Barcelona, Spain. pp.121 - 127, ⟨10.1007/978-3-319-44781-0_15⟩ Communication dans un congrès hal-01418135v1
A Deep Learning Approach for Hand Posture Recognition from Depth Data Thomas Kopinski,Fabian Sachara,Alexander Gepperth,Uwe Handmann International Conference on Artificial Neural Networks (ICANN), 2016, Barcelona, Spain. pp.179 - 186, ⟨10.1007/978-3-319-44781-0_22⟩ Communication dans un congrès hal-01418137v1
A simple technique for improving multi-class classification with neural networks Thomas Kopinski,Alexander Gepperth,Uwe Handmann European Symposium on artificial neural networks (ESANN), Jun 2015, Bruges, Belgium Communication dans un congrès hal-01251009v1
Resource-efficient incremental learning in very high dimensions Alexander Gepperth,Mathieu Lefort,Thomas Hecht,Ursula Körner European Symposium on Artificial Neural Networks (ESANN), Apr 2015, Bruges, Belgium Communication dans un congrès hal-01251015v1
Learning of local predictable representations in partially learnable environments Mathieu Lefort,Alexander Gepperth The International Joint Conference on Neural Networks (IJCNN), Jul 2015, Killarney, Ireland Communication dans un congrès hal-01205611v1
Active learning of local predictable representations with artificial curiosity Mathieu Lefort,Alexander Gepperth International Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob), Aug 2015, Providence, United States Communication dans un congrès hal-01205619v1
A light-weight real-time applicable hand gesture recognition system for automotive applications Thomas Kopinski,Stéphane Magand,Alexander Gepperth,Uwe Handmann IEEE International Symposium on Intelligent Vehicles (IV), Jun 2015, Seoul, South Korea. pp.336-342, ⟨10.1109/IVS.2015.7225708⟩ Communication dans un congrès hal-01251413v1
Using self-organizing maps for regression: the importance of the output function Thomas Hecht,Mathieu Lefort,Alexander Gepperth European Symposium on Artificial Neural Networks (ESANN), Apr 2015, Bruges, Belgium Communication dans un congrès hal-01251011v1
A generative-discriminative learning model for noisy information fusion Thomas Hecht,Alexander Gepperth International Conference on Development and Learning (ICDL), Aug 2015, Providence, United States. ⟨10.1109/DEVLRN.2015.7346148⟩ Communication dans un congrès hal-01250967v1
Biologically inspired incremental learning for high-dimensional spaces Alexander Gepperth,Thomas Hecht,Mathieu Lefort,Ursula Körner Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Sep 2015, Providence, United States. ⟨10.1109/DEVLRN.2015.7346155⟩ Communication dans un congrès hal-01250961v1
Scene context is more than a Bayesian prior: Competitive vehicle detection with restricted detectors Thomas Hecht,Mrinal Mohit,Egor Sattarov,Alexander Gepperth IEEE International Symposium on Intelligent Vehicles(IV), May 2014, Detroit, United States. pp.1358 - 1364, ⟨10.1109/IVS.2014.6856542⟩ Communication dans un congrès hal-01098707v1
Latency-Based Probabilistic Information Processing in Recurrent Neural Hierarchies Alexander Gepperth,Mathieu Lefort International Conference on Artificial Neural Networks (ICANN), Sep 2014, Hamburg, Germany. pp.715 - 722, ⟨10.1007/978-3-319-11179-7_90⟩ Communication dans un congrès hal-01098699v1
Context-based vector fields for multi-object tracking in application to road traffic Egor Sattarov,Sergio Alberto Rodriguez Florez,Alexander Gepperth,Roger Reynaud IEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.1179 - 1185, ⟨10.1109/ITSC.2014.6957847⟩ Communication dans un congrès hal-01098701v2
A real-time applicable 3D gesture recognition system for automobile HMI Thomas Kopinski,Stefan Geisler,Louis-Charles Caron,Alexander Gepperth,Uwe Handmann IEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.2616 - 2622, ⟨10.1109/ITSC.2014.6958109⟩ Communication dans un congrès hal-01098700v1
Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors Thomas Kopinski,Alexander Gepperth,Stefan Geisler,Uwe Handmann International Conference on Artificial Neural Networks (ICANN), Sep 2014, Hamburg, Germany. pp.233 - 240, ⟨10.1007/978-3-319-11179-7_30⟩ Communication dans un congrès hal-01098697v1
Neural network based 2D/3D fusion for robotic object recognition Louis-Charles Caron,Yang Song,David Filliat,Alexander Gepperth European Symposium on artificial neural networks (ESANN), May 2014, Bruges, Belgium. pp.127 - 132 Communication dans un congrès hal-01012090v1
PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discrimination Mathieu Lefort,Alexander Gepperth IJCNN - International Joint Conference on Neural Networks, Jul 2014, Pékin, China Communication dans un congrès hal-01061662v1
Latency-based probabilistic information processing in a learning feedback hierarchy Alexander Gepperth International Joint Conference on Neural Networks (IJCNN), Jun 2014, Beijing, China. pp.3031 - 3037, ⟨10.1109/IJCNN.2014.6889919⟩ Communication dans un congrès hal-01098704v1
Time-of-Flight based multi-sensor fusion strategies for hand gesture recognition Thomas Kopinski,Darius Malysiak,Alexander Gepperth,Uwe Handmann IEEE International Symposium on Computational Intelligence and Informatics, Nov 2014, Budapest, Hungary Communication dans un congrès hal-01098695v1
Robust visual pedestrian detection by tight coupling to tracking Alexander Gepperth,Egor Sattarov,Bernd Heisele,Sergio Alberto Rodriguez Florez IEEE International Conference On Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China. pp.1935 - 1940, ⟨10.1109/ITSC.2014.6957989⟩ Communication dans un congrès hal-01098703v1
Discrimination of visual pedestrians data by combining projection and prediction learning Mathieu Lefort,Alexander Gepperth European Symposium on artificial neural networks (ESANN), Apr 2014, Bruges, Belgium Communication dans un congrès hal-01061654v1
A Multi-Modal System for Road Detection and Segmentation Xiao Hu,Sergio Alberto Rodriguez Florez,Alexander Gepperth IEEE Intelligent Vehicles Symposium, Jun 2014, Dearborn, Michigan, United States. pp.1365-1370 Communication dans un congrès hal-01023615v1
Multimodal space representation driven by self-evaluation of predictability Mathieu Lefort,Thomas Kopinski,Alexander Gepperth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Oct 2014, Gênes, Italy Communication dans un congrès hal-01061668v1
Neural Network Fusion of Color, Depth and Location for Object Instance Recognition on a Mobile Robot Louis-Charles Caron,David Filliat,Alexander Gepperth Second Workshop on Assistive Computer Vision and Robotics (ACVR), in conjunction with European Conference on Computer Vision, Sep 2014, Zurich, Switzerland Communication dans un congrès hal-01087392v1
A Comparison of Geometric and Energy-Based Point Cloud Semantic Segmentation Methods Mathieu Dubois,Paola K. Rozo,Alexander Gepperth,Fabio A. González O.,David Filliat 6th European Conference on Mobile Robotics (ECMR), IEEE, Sep 2013, Barcelona, Spain. pp.88-93, ⟨10.1109/ECMR.2013.6698825⟩ Communication dans un congrès hal-00963863v1
Simultaneous concept formation driven by predictability Alexander Gepperth,Louis-Charles Caron International conference on development and learning, Nov 2012, San Diego, United States Communication dans un congrès hal-00763671v1
Co-training of context models for real-time object detection Alexander Gepperth IEEE Symposium on Intelligent Vehicles, Jun 2012, Madrid, Spain Communication dans un congrès hal-00763676v1
RGBD object recognition and visual texture classification for indoor semantic mapping David Filliat,Emmanuel Battesti,Stéphane Bazeille,Guillaume Duceux,Alexander Gepperthet al. Technologies for Practical Robot Applications (TePRA), 2012 IEEE International Conference on, Apr 2012, United States. pp.127 - 132, ⟨10.1109/TePRA.2012.6215666⟩ Communication dans un congrès hal-00755295v1

HDR (1)

New learning paradigms for real-world environment perception Alexander Gepperth Machine Learning [cs.LG]. Université Pierre & Marie Curie, 2016 HDR tel-01418147v1