Hand gesture recognition in automotive human–machine interaction using depth cameras N Zengeler, T Kopinski, U Handmann Sensors 19 (1), 59, 2018 | 97 | 2018 |
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 | 34 | 2017 |
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 | 21 | 2017 |
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 | 18 | 2015 |
Das hybride Büro: Gestaltungsansätze für New Work-Arbeitsumgebungen anhand eines Fallbeispiels C Reindl, R Lanwehr, T Kopinski Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte …, 2022 | 17 | 2022 |
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 | 15 | 2014 |
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 | 14 | 2016 |
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 | 13 | 2014 |
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 | 12 | 2015 |
A simple technique for improving multi-class classification with neural networks T Kopinski, A Gepperth, U Handmann Proceedings, 469, 2015 | 12 | 2015 |
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 | 11 | 2015 |
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 | 9 | 2016 |
Touchless interaction for future mobile applications T Kopinski, U Handmann 2016 International Conference on Computing, Networking and Communications …, 2016 | 8 | 2016 |
User expectations on touchless gestures in vehicles P März, D Schwahlen, S Geisler, T Kopinski Mensch und Computer 2016–Workshopband, 10.18420/muc2016-ws08-0002, 2016 | 8 | 2016 |
Coupled finite-element-method-simulations for real-time-process monitoring in metal forming digital-twins F Neubürger, J Arens, M Vollmer, T Kopinski, M Hermes 2022 10th International conference on control, mechatronics and automation …, 2022 | 7 | 2022 |
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 | 7 | 2014 |
Disease prediction based on individual’s medical history using CNN M Krishnamoorthy, MSA Hameed, T Kopinski, A Schwung 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 6 | 2021 |
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 | 5 | 2016 |
A real-time applicable dynamic hand gesture recognition framework T Kopinski, A Gepperth, U Handmann 2015 IEEE 18th International Conference on Intelligent Transportation …, 2015 | 5 | 2015 |
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 | 5 | 2014 |