Thomas Kopinski
Thomas Kopinski
University Ruhr West
Verified email at hs-rw.de
TitleCited byYear
A real-time applicable 3d gesture recognition system for automobile hmi
T Kopinski, S Geisler, LC Caron, A Gepperth, U Handmann
17th International IEEE Conference on Intelligent Transportation Systems …, 2014
142014
Neural network based data fusion for hand pose recognition with multiple tof sensors
T Kopinski, A Gepperth, S Geisler, U Handmann
International Conference on Artificial Neural Networks, 233-240, 2014
122014
A pragmatic approach to multi-class classification
T Kopinski, S Magand, U Handmann, A Gepperth
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
112015
A simple technique for improving multi-class classification with neural networks
T Kopinski, A Gepperth, U Handmann
Proceedings, 469, 2015
92015
A light-weight real-time applicable hand gesture recognition system for automotive applications
T Kopinski, S Magand, A Gepperth, U Handmann
2015 IEEE Intelligent Vehicles Symposium (IV), 336-342, 2015
82015
A time-of-flight-based hand posture database for human-machine interaction
T Kopinski, A Gepperth, U Handmann
2016 14th International Conference on Control, Automation, Robotics and …, 2016
62016
Touchless interaction for future mobile applications
T Kopinski, U Handmann
2016 International Conference on Computing, Networking and Communications …, 2016
62016
Gesture-based human-machine interaction for assistance systems
T Kopinski, S Geisler, U Handmann
2015 IEEE International Conference on Information and Automation, 510-517, 2015
62015
Dynamic Hand Gesture Recognition for Mobile Systems Using Deep LSTM
A Sarkar, A Gepperth, U Handmann, T Kopinski
International Conference on Intelligent Human Computer Interaction, 19-31, 2017
52017
Free-hand gesture recognition with 3D-CNNs for in-car infotainment control in real-time
F Sachara, T Kopinski, A Gepperth, U Handmann
2017 IEEE 20th International Conference on Intelligent Transportation …, 2017
52017
Time-of-flight based multi-sensor fusion strategies for hand gesture recognition
T Kopinski, D Malysiak, A Gepperth, U Handmann
2014 IEEE 15th International Symposium on Computational Intelligence and …, 2014
52014
Multimodal space representation driven by self-evaluation of predictability
M Lefort, T Kopinski, A Gepperth
4th International Conference on Development and Learning and on Epigenetic …, 2014
52014
Contactless Interaction for Automotive Applications.
T Kopinski, S Geisler, U Handmann
Mensch & Computer Workshopband, 87-94, 2013
42013
Hand gesture recognition in automotive human–machine interaction using depth cameras
N Zengeler, T Kopinski, U Handmann
Sensors 19 (1), 59, 2019
32019
A Deep Learning Approach to Mid-air Gesture Interaction for Mobile Devices from Time-of-Flight Data
T Kopinski, F Sachara, U Handmann
Proceedings of the 13th International Conference on Mobile and Ubiquitous …, 2016
32016
A Deep Learning Approach for Hand Posture Recognition from Depth Data
T Kopinski, F Sachara, A Gepperth, U Handmann
International Conference on Artificial Neural Networks, 179-186, 2016
32016
A real-time applicable dynamic hand gesture recognition framework
T Kopinski, A Gepperth, U Handmann
2015 IEEE 18th International Conference on Intelligent Transportation …, 2015
32015
Touch versus mid-air gesture interfaces in road scenarios-measuring driver performance degradation
T Kopinski, J Eberwein, S Geisler, U Handmann
2016 IEEE 19th International Conference on Intelligent Transportation …, 2016
22016
A generic and adaptive approach for workload distribution in multi-tier cluster systems with an application to distributed matrix multiplication
D Malysiak, T Kopinski
2015 16th IEEE International Symposium on Computational Intelligence and …, 2015
22015
Neural Learning Methods for Human-Computer Interaction
T Kopinski
12016
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