Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDFriedhelm Schwenker
Person information
- affiliation: Universität Ulm, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j64]Nikolai A. K. Steur
, Friedhelm Schwenker:
Class-Variational Learning With Capsule Networks for Deep Entity-Subspace Clustering. IEEE Access 11: 117368-117384 (2023)- [j63]Tobias Ricken, Peter Bellmann, Steffen Walter, Friedhelm Schwenker:
Pain Detection in Biophysiological Signals: Knowledge Transfer from Short-Term to Long-Term Stimuli Based on Distance-Specific Segment Selection. Comput. 12(4): 71 (2023) - [j62]Christopher M. A. Bonenberger, Markus Schneider, Friedhelm Schwenker, Wolfgang Ertel:
A Novel Approach to Spectral Estimation and Moving Average Model Parameter Estimation. IEEE Signal Process. Lett. 30: 1367-1371 (2023) - [c168]Fabian Erlenbusch, Constanze Merkt, Bernardo de Oliveira, Alexander Gatter, Friedhelm Schwenker, Ulrich Klauck, Michael Teutsch:
Thermal Infrared Single Image Dehazing and Blind Image Quality Assessment. CVPR Workshops 2023: 459-469 - [c167]Tobias B. Ricken, Peter Bellmann, Sascha Gruss, Hans A. Kestler, Steffen Walter, Friedhelm Schwenker:
Pain Recognition Differences between Female and Male Subjects: An Analysis based on the Physiological Signals of the X-ITE Pain Database. ICMI Companion 2023: 121-130 - [c166]Raffaela Groner, Peter Bellmann, Stefan Höppner, Patrick Thiam, Friedhelm Schwenker, Matthias Tichy:
Predicting the Performance of ATL Model Transformations. ICPE 2023: 77-89 - [e15]Taye Girma Debelee, Achim Ibenthal, Friedhelm Schwenker:
Pan-African Conference on Artificial Intelligence - First Conference, PanAfriCon AI 2022, Addis Ababa, Ethiopia, October 4-5, 2022, Revised Selected Papers. Communications in Computer and Information Science 1800, Springer 2023, ISBN 978-3-031-31326-4 [contents] - 2022
- [j61]Christopher M. A. Bonenberger, Wolfgang Ertel, Friedhelm Schwenker, Markus Schneider:
Singular Spectrum Analysis and Circulant Maximum Variance Frames. Adv. Data Sci. Adapt. Anal. 14(3&4): 2250008:1-2250008:27 (2022) - [j60]Peter Bellmann, Patrick Thiam, Hans A. Kestler, Friedhelm Schwenker:
Machine Learning-Based Pain Intensity Estimation: Where Pattern Recognition Meets Chaos Theory - An Example Based on the BioVid Heat Pain Database. IEEE Access 10: 102770-102777 (2022) - [j59]Christopher M. A. Bonenberger, Friedhelm Schwenker, Wolfgang Ertel, Markus Schneider:
Cyclic Nonlinear Correlation Analysis for Time Series. IEEE Access 10: 114223-114231 (2022) - [j58]Fraol Gelana Waldamichael, Taye Girma Debelee, Friedhelm Schwenker, Yehualashet Megersa Ayano, Samuel Rahimeto Kebede:
Machine Learning in Cereal Crops Disease Detection: A Review. Algorithms 15(3): 75 (2022) - [j57]Mehmet Erdal, Friedhelm Schwenker:
Learnability of the Boolean Innerproduct in Deep Neural Networks. Entropy 24(8): 1117 (2022) - [j56]Subhrajit Dey, Rajdeep Bhattacharya, Samir Malakar, Friedhelm Schwenker, Ram Sarkar:
CovidConvLSTM: A fuzzy ensemble model for COVID-19 detection from chest X-rays. Expert Syst. Appl. 206: 117812 (2022) - [j55]Worku Gachena Negera, Friedhelm Schwenker, Taye Girma Debelee, Henock Mulugeta Melaku, Yehualashet Megeresa Ayano:
Review of Botnet Attack Detection in SDN-Enabled IoT Using Machine Learning. Sensors 22(24): 9837 (2022) - [c165]Patrick Thiam, Hans A. Kestler, Friedhelm Schwenker:
Deep Learning Architectures for Pain Recognition Based on Physiological Signals. ICPR Workshops (1) 2022: 349-358 - [c164]Tobias Ricken, Peter Bellmann, Steffen Walter, Friedhelm Schwenker:
Pain Detection in Biophysiological Signals: Transfer Learning from Short-Term to Long-Term Stimuli Based on Signal Segmentation. ICPR Workshops (1) 2022: 394-404 - [c163]Patrick Feifel, Benedikt Franke, Arne P. Raulf, Friedhelm Schwenker, Frank Bonarens, Frank Köster:
Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection. AISafety@IJCAI 2022 - [c162]Shehabeldin Solyman, Friedhelm Schwenker:
Lung Tumor Detection and Recognition Using Deep Convolutional Neural Networks. PanAfriCon AI 2022: 79-91 - [c161]Marwan Farag, Friedhelm Schwenker:
Using Generative Adversarial Networks for Single Image Super-Resolution. PanAfriCon AI 2022: 154-168 - [c160]Christopher M. A. Bonenberger, Wolfgang Ertel, Markus Schneider, Friedhelm Schwenker:
Structured Nonlinear Discriminant Analysis. ECML/PKDD (1) 2022: 38-54 - [i7]Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler, Ahmet Selman Bozkir, Marco Calandri, Friedhelm Schwenker, Thilo Stadelmann:
PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis. CoRR abs/2208.09408 (2022) - [i6]Mohammadreza Amirian, Friedhelm Schwenker:
Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability. CoRR abs/2208.11401 (2022) - [i5]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann:
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps. CoRR abs/2208.11436 (2022) - 2021
- [j54]Nikolai A. K. Steur, Friedhelm Schwenker:
Next-Generation Neural Networks: Capsule Networks With Routing-by-Agreement for Text Classification. IEEE Access 9: 125269-125299 (2021) - [j53]Subhrajit Dey, Rajdeep Bhattacharya, Friedhelm Schwenker, Ram Sarkar:
Median Filter Aided CNN Based Image Denoising: An Ensemble Approach. Algorithms 14(4): 109 (2021) - [j52]Arne Groß, Antonia Lenders, Friedhelm Schwenker, Daniel A. Braun, David Fischer:
Comparison of short-term electrical load forecasting methods for different building types. Energy Inform. 4(S3) (2021) - [j51]Samuel Rahimeto, Taye Girma Debelee, Dereje Yohannes, Friedhelm Schwenker:
Automatic pectoral muscle removal in mammograms. Evol. Syst. 12(2): 519-526 (2021) - [j50]Erena Siyoum Biratu, Friedhelm Schwenker, Taye Girma Debelee, Samuel Rahimeto Kebede, Worku Gachena Negera, Hasset Tamirat Molla:
Enhanced Region Growing for Brain Tumor MR Image Segmentation. J. Imaging 7(2): 22 (2021) - [j49]Erena Siyoum Biratu, Friedhelm Schwenker, Yehualashet Megersa, Taye Girma Debelee:
A Survey of Brain Tumor Segmentation and Classification Algorithms. J. Imaging 7(9): 179 (2021) - [j48]Soumya Deep Roy, Soham Das, Devroop Kar, Friedhelm Schwenker, Ram Sarkar:
Computer Aided Breast Cancer Detection Using Ensembling of Texture and Statistical Image Features. Sensors 21(11): 3628 (2021) - [j47]Debadyuti Mukherjee, Koustav Dhar, Friedhelm Schwenker, Ram Sarkar:
Ensemble of Deep Learning Models for Sleep Apnea Detection: An Experimental Study. Sensors 21(16): 5425 (2021) - [j46]Patrick Thiam, Viktor Kessler, Mohammadreza Amirian, Peter Bellmann, Georg Layher, Yan Zhang, Maria Velana, Sascha Gruss, Steffen Walter, Harald C. Traue, Daniel Schork, Jonghwa Kim, Elisabeth André, Heiko Neumann, Friedhelm Schwenker:
Multi-Modal Pain Intensity Recognition Based on the SenseEmotion Database. IEEE Trans. Affect. Comput. 12(3): 743-760 (2021) - [c159]Sabine Wieluch, Friedhelm Schwenker:
Co-creative Drawing with One-Shot Generative Models. EvoMUSART 2021: 475-489 - [c158]Peter Bellmann, Heinke Hihn, Daniel A. Braun, Friedhelm Schwenker:
Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-sided Label Shifts. ICAART (2) 2021: 724-731 - [c157]Friedhelm Schwenker:
Keynote: Machine learning and data analysis of multimodal affective and pain data. PerCom Workshops 2021: 452 - 2020
- [j45]Mohammadreza Amirian, Friedhelm Schwenker:
Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability. IEEE Access 8: 123087-123097 (2020) - [j44]Peter Bellmann, Friedhelm Schwenker:
Ordinal Classification: Working Definition and Detection of Ordinal Structures. IEEE Access 8: 164380-164391 (2020) - [j43]Shameem Ahmed, Kushal Kanti Ghosh, Suman Kumar Bera, Friedhelm Schwenker, Ram Sarkar:
Gray Level Image Contrast Enhancement Using Barnacles Mating Optimizer. IEEE Access 8: 169196-169214 (2020) - [j42]Taye Girma Debelee, Friedhelm Schwenker, Achim Ibenthal, Dereje Yohannes:
Survey of deep learning in breast cancer image analysis. Evol. Syst. 11(1): 143-163 (2020) - [j41]Taye Girma Debelee, Samuel Rahimeto Kebede, Friedhelm Schwenker, Zemene Matewos Shewarega:
Deep Learning in Selected Cancers' Image Analysis - A Survey. J. Imaging 6(11): 121 (2020) - [j40]Shibaprasad Sen, Shubham Chowdhury, Mridul Mitra, Friedhelm Schwenker, Ram Sarkar, Kaushik Roy:
A novel segmentation technique for online handwritten Bangla words. Pattern Recognit. Lett. 139: 26-33 (2020) - [j39]Patrick Thiam, Hans A. Kestler, Friedhelm Schwenker:
Two-Stream Attention Network for Pain Recognition from Video Sequences. Sensors 20(3): 839 (2020) - [j38]Dilana Hazer-Rau, Sascha Meudt, Andreas Daucher, Jennifer Spohrs, Holger Hoffmann, Friedhelm Schwenker, Harald C. Traue:
The uulmMAC Database - A Multimodal Affective Corpus for Affective Computing in Human-Computer Interaction. Sensors 20(8): 2308 (2020) - [c156]Tobias Ricken, Adrian Steinert, Peter Bellmann, Steffen Walter, Friedhelm Schwenker:
Feature Extraction: A Time Window Analysis Based on the X-ITE Pain Database. ANNPR 2020: 138-148 - [c155]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Pain Intensity Recognition - An Analysis of Short-Time Sequences in a Real-World Scenario. ANNPR 2020: 149-161 - [c154]Jasmin Dalferth, Sven Winkelmann, Friedhelm Schwenker:
Using Mask R-CNN for Image-Based Wear Classification of Solid Carbide Milling and Drilling Tools. ANNPR 2020: 223-234 - [c153]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Automatic Pain Intensity Recognition: Training Set Selection based on Outliers and Centroids. ESANN 2020: 649-654 - [c152]Rajdeep Bhattacharya, Samir Malakar, Friedhelm Schwenker, Ram Sarkar:
Fuzzy-Based Pseudo Segmentation Approach for Handwritten Word Recognition Using a Sequence to Sequence Model with Attention. ICPR Workshops (2) 2020: 582-596 - [c151]Peter Bellmann, Ludwig Lausser, Hans A. Kestler, Friedhelm Schwenker:
Introducing Bidirectional Ordinal Classifier Cascades Based on a Pain Intensity Recognition Scenario. ICPR Workshops (6) 2020: 773-787 - [c150]Youssef Wally, Yara Samaha, Ziad Yasser, Steffen Walter, Friedhelm Schwenker:
Personalized k-fold Cross-Validation Analysis with Transfer from Phasic to Tonic Pain Recognition on X-ITE Pain Database. ICPR Workshops (6) 2020: 788-802 - [c149]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Using Meta Labels for the Training of Weighting Models in a Sample-Specific Late Fusion Classification Architecture. ICPR 2020: 2604-2611 - [c148]Anuran Chakraborty, Rajonya De, Samir Malakar, Friedhelm Schwenker, Ram Sarkar:
Handwritten Digit String Recognition using Deep Autoencoder based Segmentation and ResNet based Recognition Approach. ICPR 2020: 7737-7742 - [c147]Nadeen Shoukry, Omar Elkilany, Patrick Thiam, Viktor Kessler, Friedhelm Schwenker:
Subject-independent Pain Recognition using Physiological Signals and Para-linguistic Vocalizations. ICPRAM 2020: 142-150 - [c146]Patrick Thiam, Hans A. Kestler, Friedhelm Schwenker:
Multimodal Deep Denoising Convolutional Autoencoders for Pain Intensity Classification based on Physiological Signals. ICPRAM 2020: 289-296 - [c145]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Person Identification based on Physiological Signals: Conditions and Risks. ICPRAM 2020: 373-380 - [c144]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Dominant Channel Fusion Architectures - An Intelligent Late Fusion Approach. IJCNN 2020: 1-8 - [c143]Peter Bellmann, Friedhelm Schwenker:
Automated Pain Assessment: Is it Useful to Combine Person-Specific Data Samples? SSCI 2020: 1588-1593 - [c142]Peter Bellmann, Ludwig Lausser, Hans A. Kestler, Friedhelm Schwenker:
Experimental Analysis of Bidirectional Pairwise Ordinal Classifier Cascades. S+SSPR 2020: 55-64 - [c141]Mohammadreza Amirian, Lukas Tuggener, Ricardo Chavarriaga, Yvan Putra Satyawan, Frank-Peter Schilling, Friedhelm Schwenker, Thilo Stadelmann:
Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness. TAILOR 2020: 268-275 - [i4]Sabine Wieluch, Friedhelm Schwenker:
StrokeCoder: Path-Based Image Generation from Single Examples using Transformers. CoRR abs/2003.11958 (2020) - [i3]Peter Bellmann, Heinke Hihn, Daniel A. Braun, Friedhelm Schwenker:
Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-Sided Label Shifts. CoRR abs/2011.14764 (2020)
2010 – 2019
- 2019
- [j37]Taye Girma Debelee, Friedhelm Schwenker, Samuel Rahimeto, Dereje Yohannes:
Evaluation of modified adaptive k-means segmentation algorithm. Comput. Vis. Media 5(4): 347-361 (2019) - [j36]Günther Palm, Friedhelm Schwenker:
Artificial Development by Reinforcement Learning Can Benefit From Multiple Motivations. Frontiers Robotics AI 6: 6 (2019) - [j35]Shibaprasad Sen, Mridul Mitra, Ankan Bhattacharyya, Ram Sarkar, Friedhelm Schwenker, Kaushik Roy:
Feature Selection for Recognition of Online Handwritten Bangla Characters. Neural Process. Lett. 50(3): 2281-2304 (2019) - [j34]Patrick Thiam, Peter Bellmann, Hans A. Kestler, Friedhelm Schwenker:
Exploring Deep Physiological Models for Nociceptive Pain Recognition. Sensors 19(20): 4503 (2019) - [j33]Karan Sharma, Marius Wagner, Claudio Castellini, Egon L. van den Broek, Freek Stulp, Friedhelm Schwenker:
A functional data analysis approach for continuous 2-D emotion annotations. Web Intell. 17(1): 41-52 (2019) - [c140]Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Using a Quartile-based Data Transformation for Pain Intensity Classification based on the SenseEmotion Database. ACII Workshops 2019: 310-316 - [c139]Nikolai Kalischek, Patrick Thiam, Peter Bellmann, Friedhelm Schwenker:
Deep Domain Adaptation for Facial Expression Analysis. ACII Workshops 2019: 317-323 - [c138]Anuran Chakraborty, Rajonya De, Agneet Chatterjee, Friedhelm Schwenker, Ram Sarkar:
Filter Method Ensemble with Neural Networks. ICANN (2) 2019: 755-765 - [c137]Sabine Wieluch, Friedhelm Schwenker:
Dropout Induced Noise for Co-Creative GAN Systems. ICCV Workshops 2019: 3137-3140 - [e14]Friedhelm Schwenker, Stefan Scherer:
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 5th IAPR TC 9 Workshop, MPRSS 2018, Beijing, China, August 20, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11377, Springer 2019, ISBN 978-3-030-20983-4 [contents] - [i2]Sabine Wieluch, Friedhelm Schwenker:
Dropout Induced Noise for Co-Creative GAN Systems. CoRR abs/1909.04474 (2019) - 2018
- [j32]Edmondo Trentin, Friedhelm Schwenker, Neamat El Gayar, Hazem M. Abbas:
Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition. Neural Process. Lett. 48(2): 643-648 (2018) - [j31]Patrick Thiam, Sascha Meudt, Günther Palm, Friedhelm Schwenker:
A Temporal Dependency Based Multi-modal Active Learning Approach for Audiovisual Event Detection. Neural Process. Lett. 48(2): 709-732 (2018) - [c136]Ludwig Lausser, Robin Szekely, Viktor Kessler, Friedhelm Schwenker, Hans A. Kestler:
Selecting Features from Foreign Classes. ANNPR 2018: 66-77 - [c135]Adrián T. Ruiz, Patrick Thiam, Friedhelm Schwenker, Günther Palm:
A k -Nearest Neighbor Based Algorithm for Multi-Instance Multi-Label Active Learning. ANNPR 2018: 139-151 - [c134]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann:
Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps. ANNPR 2018: 346-358 - [c133]Adrián T. Ruiz, Julian Equihua, Santiago Martínez, Everardo Robredo, Günther Palm, Friedhelm Schwenker:
Detection of Bat Acoustics Signals Using Voice Activity Detection Techniques with Random Forests Classification. CIARP 2018: 253-261 - [c132]Patrick Thiam, Friedhelm Schwenker:
Combining Deep and Hand-Crafted Features for Audio-Based Pain Intensity Classification. MPRSS 2018: 49-58 - [c131]Venkatesh Srinivasan, Sascha Meudt, Friedhelm Schwenker:
Deep Learning Algorithms for Emotion Recognition on Low Power Single Board Computers. MPRSS 2018: 59-70 - [c130]Danila Mamontov, Iana Polonskaia, Alina Skorokhod, Eugene Semenkin, Viktor Kessler, Friedhelm Schwenker:
Evolutionary Algorithms for the Design of Neural Network Classifiers for the Classification of Pain Intensity. MPRSS 2018: 84-100 - [c129]Jan Sellner, Patrick Thiam, Friedhelm Schwenker:
Visualizing Facial Expression Features of Pain and Emotion Data. MPRSS 2018: 101-115 - [e13]Luca Pancioni, Friedhelm Schwenker, Edmondo Trentin:
Artificial Neural Networks in Pattern Recognition - 8th IAPR TC3 Workshop, ANNPR 2018, Siena, Italy, September 19-21, 2018, Proceedings. Lecture Notes in Computer Science 11081, Springer 2018, ISBN 978-3-319-99977-7 [contents] - [i1]Karan Sharma, Claudio Castellini, Egon L. van den Broek, Alin Albu-Schäffer, Friedhelm Schwenker:
A dataset of continuous affect annotations and physiological signals for emotion analysis. CoRR abs/1812.02782 (2018) - 2017
- [j30]Markus Kächele, Mohammadreza Amirian, Patrick Thiam, Philipp Werner, Steffen Walter, Günther Palm, Friedhelm Schwenker:
Adaptive confidence learning for the personalization of pain intensity estimation systems. Evol. Syst. 8(1): 71-83 (2017) - [c128]Viktor Kessler, Patrick Thiam, Mohammadreza Amirian, Friedhelm Schwenker:
Multimodal fusion including camera photoplethysmography for pain recognition. ICCT 2017: 1-4 - [c127]Patrick Thiam, Viktor Kessler, Friedhelm Schwenker:
Hierarchical Combination of Video Features for Personalised Pain Level Recognition. ESANN 2017 - [c126]Mohammadreza Amirian, Markus Kächele, Günther Palm, Friedhelm Schwenker:
Support Vector Regression of Sparse Dictionary-Based Features for View-Independent Action Unit Intensity Estimation. FG 2017: 854-859 - [c125]Taye Girma Debelee, Mohammadreza Amirian, Achim Ibenthal, Günther Palm, Friedhelm Schwenker:
Classification of Mammograms Using Convolutional Neural Network Based Feature Extraction. ICT4DA 2017: 89-98 - [c124]Viktor Kessler, Patrick Thiam, Mohammadreza Amirian, Friedhelm Schwenker:
Pain recognition with camera photoplethysmography. IPTA 2017: 1-5 - [c123]Patrick Thiam, Friedhelm Schwenker:
Multi-modal data fusion for pain intensity assessment and classification. IPTA 2017: 1-6 - [p9]Friedhelm Schwenker, Ronald Böck, Martin Schels, Sascha Meudt, Ingo Siegert, Michael Glodek, Markus Kächele, Miriam Schmidt-Wack, Patrick Thiam, Andreas Wendemuth, Gerald Krell:
Multimodal Affect Recognition in the Context of Human-Computer Interaction for Companion-Systems. Companion Technology 2017: 387-408 - [p8]Andreas Wendemuth, Bogdan Vlasenko, Ingo Siegert, Ronald Böck, Friedhelm Schwenker, Günther Palm:
Emotion Recognition from Speech. Companion Technology 2017: 409-428 - [p7]Ingo Siegert, Felix Schüssel, Miriam Schmidt, Stephan Reuter, Sascha Meudt, Georg Layher, Gerald Krell, Thilo Hörnle, Sebastian Handrich, Ayoub Al-Hamadi, Klaus Dietmayer, Heiko Neumann, Günther Palm, Friedhelm Schwenker, Andreas Wendemuth:
Multi-modal Information Processing inCompanion-Systems: A Ticket Purchase System. Companion Technology 2017: 493-500 - [e12]Friedhelm Schwenker, Stefan Scherer:
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers. Lecture Notes in Computer Science 10183, Springer 2017, ISBN 978-3-319-59258-9 [contents] - 2016
- [j29]Markus Kächele, Martin Schels, Friedhelm Schwenker:
The Influence of Annotation, Corpus Design, and Evaluation on the Outcome of Automatic Classification of Human Emotions. Frontiers ICT 3: 27 (2016) - [j28]Markus Kächele, Martin Schels, Sascha Meudt, Günther Palm, Friedhelm Schwenker:
Revisiting the EmotiW challenge: how wild is it really? J. Multimodal User Interfaces 10(2): 151-162 (2016) - [j27]Markus Kächele, Patrick Thiam, Mohammadreza Amirian, Friedhelm Schwenker, Günther Palm:
Methods for Person-Centered Continuous Pain Intensity Assessment From Bio-Physiological Channels. IEEE J. Sel. Top. Signal Process. 10(5): 854-864 (2016) - [c122]Mohammadreza Amirian, Markus Kächele, Friedhelm Schwenker:
Using Radial Basis Function Neural Networks for Continuous and Discrete Pain Estimation from Bio-physiological Signals. ANNPR 2016: 269-284 - [c121]Patrick Thiam, Sascha Meudt, Friedhelm Schwenker, Günther Palm:
Active Learning for Speech Event Detection in HCI. ANNPR 2016: 285-297 - [c120]Mehmet Erdal, Markus Kächele, Friedhelm Schwenker:
Emotion Recognition in Speech with Deep Learning Architectures. ANNPR 2016: 298-311 - [c119]Heinke Hihn, Sascha Meudt, Friedhelm Schwenker:
On Gestures and Postural Behavior as a Modality in Ensemble Methods. ANNPR 2016: 312-323 - [c118]Viktor Kessler, Markus Kächele, Sascha Meudt, Friedhelm Schwenker, Günther Palm:
Machine Learning Driven Heart Rate Detection with Camera Photoplethysmography in Time Domain. ANNPR 2016: 324-334 - [c117]Heinke Hihn, Sascha Meudt, Friedhelm Schwenker:
Inferring mental overload based on postural behavior and gestures. ERM4CT@ICMI 2016: 3:1-3:4 - [c116]Mohammadreza Amirian, Markus Kächele, Patrick Thiam, Viktor Kessler, Friedhelm Schwenker:
Continuous Multimodal Human Affect Estimation using Echo State Networks. AVEC@ACM Multimedia 2016: 67-74 - [c115]Dennis Held, Sascha Meudt, Friedhelm Schwenker:
Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes. MPRSS 2016: 12-23 - [c114]Daniel Kindsvater, Sascha Meudt, Friedhelm Schwenker:
Fusion Architectures for Multimodal Cognitive Load Recognition. MPRSS 2016: 36-47 - [c113]Patrick Thiam, Viktor Kessler, Steffen Walter, Günther Palm, Friedhelm Schwenker:
Audio-Visual Recognition of Pain Intensity. MPRSS 2016: 110-126 - [c112]Maria Velana, Sascha Gruss, Georg Layher,