Friedhelm Schwenker

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Günther PalmProfessor für Neuroinformatik, Universität UlmVerified email at uni-ulm.de
Hans A. KestlerProfessor, Institute of Medical Systems Biology, Ulm UniversityVerified email at uni-ulm.de
Patrick ThiamInstitute of Neural Information Processing, Ulm University, GermanyVerified email at uni-ulm.de
Markus KächeleInstitute of Neural Information Processing, Ulm UniversityVerified email at uni-ulm.de
Stefan SchererMeta - Reality Labs ResearchVerified email at fb.com
Michael GlodekInstitute of Neural Information Processing, University of UlmVerified email at zguy.de
sascha meudtulm universityVerified email at uni-ulm.de
Heiko NeumannProfessor for Computer Science, Ulm University, Institute of Neural Information ProcessingVerified email at uni-ulm.de
Georg LayherInstitute of Neural Information Processing, Ulm UniversityVerified email at yher.de
Stefan FaußerNeu-Ulm University of Applied Science (HNU)Verified email at hnu.de
Tobias BroschHensoldt Sensors GmbHVerified email at hensoldt.net
Friedrich T SommerUC BerkeleyVerified email at berkeley.edu
Philipp WernerUniversity of MagdeburgVerified email at ovgu.de
Klaus Riede(former) Senior scientist at Zoological Research Museum BonnVerified email at uni-bonn.de
Ronald BöckOtto von Guericke University MagdeburgVerified email at ovgu.de
Ayoub Al-HamadiProfessor of Neuro-Information Technology (NIT)Verified email at ovgu.de
Nick CampbellATR, NAIST, NiCT,TCDVerified email at tcd.ie
Stephan ReuterSensor Fusion for Urban Automated Driving, Robert Bosch GmbHVerified email at stephanreuter.de
Klaus DietmayerProfessor für Mess- und RegelungstechnikVerified email at uni-ulm.de
Ingo SiegertMobile Dialog Systems, IIKT, Otto von Guericke University MagdeburgVerified email at ovgu.de

Friedhelm Schwenker

Ulm University, Institute of Neural Information Processing

Verified email at uni-ulm.de

neural networks machine learning pattern recognition data mining affective computing


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Three learning phases for radial-basis-function networks F Schwenker, HA Kestler, G Palm Neural networks 14 (4-5), 439-458, 2001	631	2001
Pattern classification and clustering: A review of partially supervised learning approaches F Schwenker, E Trentin Pattern Recognition Letters 37, 4-14, 2014	235	2014
Hierarchical support vector machines for multi-class pattern recognition F Schwenker Knowledge-Based Intelligent Engineering Systems and Allied Technologies …, 2000	174	2000
Multiple classifier systems for the classification of audio-visual emotional states M Glodek, S Tschechne, G Layher, M Schels, T Brosch, S Scherer, ... Affective Computing and Intelligent Interaction, 359-368, 2011	152	2011
Iterative retrieval of sparsely coded associative memory patterns F Schwenker, FT Sommer, G Palm Neural Networks 9 (3), 445-455, 1996	141	1996
Semi-supervised learning MFA Hady, F Schwenker Handbook on Neural Information Processing, 215-239, 2013	119	2013
Survey of deep learning in breast cancer image analysis TG Debelee, F Schwenker, A Ibenthal, D Yohannes Evolving Systems 11, 143-163, 2020	99	2020
Investigating fuzzy-input fuzzy-output support vector machines for robust voice quality classification S Scherer, J Kane, C Gobl, F Schwenker Computer Speech & Language 27 (1), 263-287, 2013	88	2013
Neural associative memory G Palm, F Schwenker, FT Sommer, A Strey, F Kurfeß Associative processing and processors, 1997	87	1997
A study of the robustness of KNN classifiers trained using soft labels N El Gayar, F Schwenker, G Palm Artificial Neural Networks in Pattern Recognition: Second IAPR Workshop …, 2006	86	2006
A dataset of continuous affect annotations and physiological signals for emotion analysis K Sharma, C Castellini, EL van den Broek, A Albu-Schaeffer, ... Scientific data 6 (1), 196, 2019	85	2019
De-noising of high-resolution ECG signals by combining the discrete wavelet transform with the Wiener filter HA Kestler, M Haschka, W Kratz, F Schwenker, G Palm, V Hombach, ... Computers in Cardiology 1998. Vol. 25 (Cat. No. 98CH36292), 233-236, 1998	79	1998
Multimodal emotion classification in naturalistic user behavior S Walter, S Scherer, M Schels, M Glodek, D Hrabal, M Schmidt, R Böck, ... Human-Computer Interaction. Towards Mobile and Intelligent Interaction …, 2011	78	2011
Combining committee-based semi-supervised learning and active learning M Farouk Abdel Hady, F Schwenker Journal of Computer Science and Technology 25 (4), 681-698, 2010	77	2010
Adaptive confidence learning for the personalization of pain intensity estimation systems M Kächele, M Amirian, P Thiam, P Werner, S Walter, G Palm, ... Evolving Systems 8, 71-83, 2017	73	2017
Methods for person-centered continuous pain intensity assessment from bio-physiological channels M Kächele, P Thiam, M Amirian, F Schwenker, G Palm IEEE Journal of Selected Topics in Signal Processing 10 (5), 854-864, 2016	72	2016
Co-training by committee: a new semi-supervised learning framework MFA Hady, F Schwenker 2008 IEEE International Conference on Data Mining Workshops, 563-572, 2008	68	2008
Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression M Kächele, M Glodek, D Zharkov, S Meudt, F Schwenker depression 1 (1), 671-678, 2014	66	2014
The senseemotion database: A multimodal database for the development and systematic validation of an automatic pain-and emotion-recognition system M Velana, S Gruss, G Layher, P Thiam, Y Zhang, D Schork, V Kessler, ... Multimodal Pattern Recognition of Social Signals in Human-Computer …, 2017	61	2017
Multimodal data fusion for person-independent, continuous estimation of pain intensity M Kächele, P Thiam, M Amirian, P Werner, S Walter, F Schwenker, ... Engineering Applications of Neural Networks: 16th International Conference …, 2015	60	2015

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