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Mohammadreza Amirian
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2020 – today
- 2024
- [j7]Mohammadreza Amirian
, Daniel Barco
Artifact Reduction in 3D and 4D Cone-Beam Computed Tomography Images With Deep Learning: A Review. IEEE Access 12: 10281-10295 (2024) - [i8]Mohammadreza Amirian, Daniel Barco, Ivo Herzig, Frank-Peter Schilling:
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning - A Review. CoRR abs/2403.18565 (2024) - [i7]Mohammadreza Amirian:
Deep Learning for Robust and Explainable Models in Computer Vision. CoRR abs/2403.18674 (2024) - 2023
- [b1]Mohammadreza Amirian:
Deep Learning for Robust and Explainable Models in Computer Vision. University of Ulm, Germany, 2023 - 2022
- [j6]Samuel Wehrli
Bias, awareness, and ignorance in deep-learning-based face recognition. AI Ethics 2(3): 509-522 (2022) - [i6]Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler, Ahmet Selman Bozkir
PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis. CoRR abs/2208.09408 (2022) - [i5]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) - [i4]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann:
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps. CoRR abs/2208.11436 (2022) - 2021
- [j5]Patrick Thiam
Multi-Modal Pain Intensity Recognition Based on the SenseEmotion Database. IEEE Trans. Affect. Comput. 12(3): 743-760 (2021) - [c14]Mohammadreza Amirian, Javier A. Montoya-Zegarra
PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis. CISP-BMEI 2021: 1-7 - 2020
- [j4]Mohammadreza Amirian
Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability. IEEE Access 8: 123087-123097 (2020) - [c13]Stefan Glüge
How (Not) to Measure Bias in Face Recognition Networks. ANNPR 2020: 125-137 - [c12]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
2010 – 2019
- 2019
- [c11]Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, Thilo Stadelmann
Automated Machine Learning in Practice: State of the Art and Recent Results. SDS 2019: 31-36 - [p1]Lukas Hollenstein
Unsupervised Learning and Simulation for Complexity Management in Business Operations. Applied Data Science 2019: 313-331 - [i3]Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, Thilo Stadelmann:
Automated Machine Learning in Practice: State of the Art and Recent Results. CoRR abs/1907.08392 (2019) - 2018
- [c10]Thilo Stadelmann
Deep Learning in the Wild. ANNPR 2018: 17-38 - [c9]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Dürr, Thilo Stadelmann
Learning Neural Models for End-to-End Clustering. ANNPR 2018: 126-138 - [c8]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann
Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps. ANNPR 2018: 346-358 - [i2]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Durr, Thilo Stadelmann:
Learning Neural Models for End-to-End Clustering. CoRR abs/1807.04001 (2018) - [i1]Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald, Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener:
Deep Learning in the Wild. CoRR abs/1807.04950 (2018) - 2017
- [j3]Markus Kächele, Mohammadreza Amirian, Patrick Thiam
Adaptive confidence learning for the personalization of pain intensity estimation systems. Evol. Syst. 8(1): 71-83 (2017) - [c7]Viktor Kessler, Patrick Thiam, Mohammadreza Amirian, Friedhelm Schwenker:
Multimodal fusion including camera photoplethysmography for pain recognition. ICCT 2017: 1-4 - [c6]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 - [c5]Taye Girma Debelee
Classification of Mammograms Using Convolutional Neural Network Based Feature Extraction. ICT4DA 2017: 89-98 - [c4]Viktor Kessler, Patrick Thiam, Mohammadreza Amirian, Friedhelm Schwenker:
Pain recognition with camera photoplethysmography. IPTA 2017: 1-5 - 2016
- [j2]Markus Kächele, Patrick Thiam
Methods for Person-Centered Continuous Pain Intensity Assessment From Bio-Physiological Channels. IEEE J. Sel. Top. Signal Process. 10(5): 854-864 (2016) - [c3]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 - [c2]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 - 2015
- [c1]Markus Kächele, Patrick Thiam, Mohammadreza Amirian, Philipp Werner, Steffen Walter, Friedhelm Schwenker, Günther Palm:
Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity. EANN 2015: 275-285 - 2014
- [j1]Kamran Kazemi, Mohammadreza Amirian, Mohammad Javad Dehghani
The S-transform using a new window to improve frequency and time resolutions. Signal Image Video Process. 8(3): 533-541 (2014)
Coauthor Index
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last updated on 2024-08-05 21:19 CEST by the dblp team
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