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
Markus KächeleInstitute of Neural Information Processing, Ulm UniversityVerified email at uni-ulm.de
Stefan SchererCTO - Embodied, Inc.Verified email at embodied.me
Michael GlodekInstitute of Neural Information Processing, University of UlmVerified email at zguy.de
Patrick ThiamInstitute of Neural Information Processing, Ulm University, GermanyVerified email at uni-ulm.de
sascha meudtulm universityVerified email at uni-ulm.de
Mohamed Farouk Abdel HadySenior Applied Science Manager, Alexa AI, AmazonVerified email at amazon.com
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
Ronald BöckOtto von Guericke University MagdeburgVerified email at ovgu.de
Klaus Riede(former) Senior scientist at Zoological Research Museum BonnVerified email at uni-bonn.de
Nick CampbellATR, NAIST, NiCT,TCDVerified email at tcd.ie
Ayoub Al-HamadiVerified email at ovgu.de
Ingo SiegertMobile Dialog Systems, IIKT, Otto von Guericke University MagdeburgVerified email at ovgu.de
Andreas WendemuthProfessor for Cognitive Systems, 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	587	2001
Pattern classification and clustering: A review of partially supervised learning approaches F Schwenker, E Trentin Pattern Recognition Letters 37, 4-14, 2014	195	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	149	2011
Iterative retrieval of sparsely coded associative memory patterns F Schwenker, FT Sommer, G Palm Neural Networks 9 (3), 445-455, 1996	134	1996
Semi-supervised learning MFA Hady, F Schwenker Handbook on Neural Information Processing, 215-239, 2013	96	2013
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	85	2013
Neural associative memory G Palm, F Schwenker, FT Sommer, A Strey, F Kurfeß Associative processing and processors, 1997	84	1997
Multimodal emotion classification in naturalistic user behavior S Walter, S Scherer, M Schels, M Glodek, D Hrabal, M Schmidt, R Böck, ... International Conference on Human-Computer Interaction, 603-611, 2011	79	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	76	2010
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	76	1998
A study of the robustness of KNN classifiers trained using soft labels NE Gayar, F Schwenker, G Palm IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 67-80, 2006	70	2006
Decision templates for the classification of bioacoustic time series C Dietrich, G Palm, F Schwenker Information Fusion 4 (2), 101-109, 2003	64	2003
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	63	2014
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	63	2008
Survey of deep learning in breast cancer image analysis TG Debelee, F Schwenker, A Ibenthal, D Yohannes Evolving Systems 11 (1), 143-163, 2020	62	2020
Spotting laughter in natural multiparty conversations: A comparison of automatic online and offline approaches using audiovisual data S Scherer, M Glodek, F Schwenker, N Campbell, G Palm ACM Trans. Interact. Intell. Syst 2 (1), 4, 2013	60	2013
Inferring depression and affect from application dependent meta knowledge M Kächele, M Schels, F Schwenker Proceedings of the 4th International Workshop on Audio/Visual Emotion …, 2014	58	2014
A generic framework for the inference of user states in human computer interaction S Scherer, M Glodek, G Layher, M Schels, M Schmidt, T Brosch, ... Journal on Multimodal User Interfaces 6 (3), 117-141, 2012	57	2012
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 (1), 71-83, 2017	56	2017

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