mohammadreza amirian
mohammadreza amirian
Research assistant, Zurich University of Applied Sciences (ZHAW)
Verified email at - Homepage
Cited by
Cited by
Automated machine learning in practice: state of the art and recent results
L Tuggener, M Amirian, K Rombach, S Lörwald, A Varlet, C Westermann, ...
2019 6th Swiss Conference on Data Science (SDS), 31-36, 2019
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
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
Multi-Modal Pain Intensity Recognition Based on the SenseEmotion Database
P Thiam, V Kessler, M Amirian, P Bellmann, G Layher, Y Zhang, M Velana, ...
IEEE Transactions on Affective Computing 12 (3), 743-760, 2019
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
Classification of mammograms using texture and CNN based extracted features
TG Debelee, A Gebreselasie, F Schwenker, M Amirian, D Yohannes
Journal of Biomimetics, Biomaterials and Biomedical Engineering 42, 79-97, 2019
Deep learning in the wild
T Stadelmann, M Amirian, I Arabaci, M Arnold, GF Duivesteijn, I Elezi, ...
Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018
Classification of mammograms using convolutional neural network based feature extraction
TG Debelee, M Amirian, A Ibenthal, G Palm, F Schwenker
International Conference on Information and Communication Technology for …, 2017
Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability
M Amirian, F Schwenker
IEEE Access 8, 123087-123097, 2020
Learning neural models for end-to-end clustering
BB Meier, I Elezi, M Amirian, O Dürr, T Stadelmann
Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018
Bias, awareness, and ignorance in deep-learning-based face recognition
S Wehrli, C Hertweck, M Amirian, S Glüge, T Stadelmann
AI and Ethics 2 (3), 509-522, 2022
Pain recognition with camera photoplethysmography
V Kessler, P Thiam, M Amirian, F Schwenker
2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017
The S-transform using a new window to improve frequency and time resolutions
K Kazemi, M Amirian, MJ Dehghani
Signal, image and Video processing 8 (3), 533-541, 2014
Using radial basis function neural networks for continuous and discrete pain estimation from bio-physiological signals
M Amirian, M Kächele, F Schwenker
Artificial Neural Networks in Pattern Recognition: 7th IAPR TC3 Workshop …, 2016
How (not) to measure bias in face recognition networks
S Glüge, M Amirian, D Flumini, T Stadelmann
IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 125-137, 2020
Support vector regression of sparse dictionary-based features for view-independent action unit intensity estimation
M Amirian, M Kächele, G Palm, F Schwenker
2017 12th IEEE International Conference on Automatic Face & Gesture …, 2017
Trace and detect adversarial attacks on CNNs using feature response maps
M Amirian, F Schwenker, T Stadelmann
Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018
Continuous multimodal human affect estimation using echo state networks
M Amirian, M Kächele, P Thiam, V Kessler, F Schwenker
Proceedings of the 6th International Workshop on Audio/Visual Emotion …, 2016
Multimodal fusion including camera photoplethysmography for pain recognition
V Kessler, P Thiam, M Amirian, F Schwenker
2017 International Conference on Companion Technology (ICCT), 1-4, 2017
Design patterns for resource-constrained automated deep-learning methods
L Tuggener, M Amirian, F Benites, P von Däniken, P Gupta, FP Schilling, ...
AI 1 (4), 510-538, 2020
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