Mohammadreza Amirian

Mohammadreza Amirian
ZHAW
School of Engineering
Centre for Artificial Intelligence
Technikumstrasse 71
8400 Winterthur
Persönliches Profil
Tätigkeit an der ZHAW
Wissenschaftlicher Assistent
Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse
Maschinelles Lernen, Mustererkennung, Neuronale Netze, Affective Computing, Gesichtsausdruck, Computer Vision, Digitale Signalverarbeitung, Bio-Physiologische Signalverarbeitung, Schmerzschätzung, Sonar, Bildverarbeitung, Komprimierte Erkennung, Medizinische Bildgebung, Multi-modale DatenFusion, Recurrent Networks
Aktuelle Forschungsinteressen: Deep Learning, Bildverarbeitung
Aus- und Fortbildung
Master, Kommunikationstechnik, 2017, Universität Ulm
Projekte
- AC3T – AI powered CBCT for improved Combination Cancer Therapy / Teammitglied / Projekt laufend
- TAILOR – Trustworthy and sample efficient vision transformers / ProjektleiterIn / Projekt abgeschlossen
- Synthetic data generation of CoVID-19 CT/X-rays images for enabling fast triage of healthy vs. unhealthy patients / Teammitglied / Projekt abgeschlossen
- Standardized Data and Modeling for AI-based CoVID-19 Diagnosis Support on CT Scans (SDMCT) / ProjektleiterIn / Projekt abgeschlossen
- DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Teammitglied / Projekt abgeschlossen
- TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization / Teammitglied / Projekt abgeschlossen
- FWA: Visual Food Waste Analysis for Sustainable Kitchens / Teammitglied / Projekt abgeschlossen
- Ada – Advanced Algorithms for an Artificial Data Analyst / Teammitglied / Projekt abgeschlossen
- QualitAI - Quality control of industrial products via deep learning on images / Teammitglied / Projekt abgeschlossen
- Libra: A One-Tool Solution for MLD4 Compliance / Teammitglied / Projekt abgeschlossen
- Complexity 4.0 / Teammitglied / Projekt abgeschlossen
Publikationen
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Wehrli, Samuel; Hertweck, Corinna; Amirian, Mohammadreza; Glüge, Stefan; Stadelmann, Thilo,
2021.
Bias, awareness, and ignorance in deep-learning-based face recognition.
AI and Ethics.
2(3), S. 509-522.
Verfügbar unter: https://doi.org/10.1007/s43681-021-00108-6
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Thiam, Patrick; Kessler, Viktor; Amirian, Mohammadreza; Bellmann, Peter; Layher, Georg; Zhang, Yan; Velana, Maria; Gruss, Sascha; Walter, Steffen; Traue, Harald C.; Schork, Daniel; Kim, Jonghwa; Andre, Elisabeth; Neumann, Heiko; Schwenker, Friedhelm,
2021.
Multi-modal pain intensity recognition based on the SenseEmotion database.
IEEE Transactions on Affective Computing.
12(3), S. 743-760.
Verfügbar unter: https://doi.org/10.1109/TAFFC.2019.2892090
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Tuggener, Lukas; Amirian, Mohammadreza; Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Gupta, Prakhar; Schilling, Frank-Peter; Stadelmann, Thilo,
2020.
Design patterns for resource-constrained automated deep-learning methods.
AI.
1(4), S. 510-538.
Verfügbar unter: https://doi.org/10.3390/ai1040031
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Amirian, Mohammadreza; Schwenker, Friedhelm,
2020.
IEEE Access.
8, S. 123087-123097.
Verfügbar unter: https://doi.org/10.1109/ACCESS.2020.3007337
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Hollenstein, Lukas; Lichtensteiger, Lukas; Stadelmann, Thilo; Amirian, Mohammadreza; Budde, Lukas; Meierhofer, Jürg; Füchslin, Rudolf Marcel; Friedli, Thomas,
2019.
Unsupervised learning and simulation for complexity management in business operations
.
In:
Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, Hrsg.,
Applied data science : lessons learned for the data-driven business.
Cham:
Springer.
S. 313-331.
Verfügbar unter: https://doi.org/10.1007/978-3-030-11821-1_17
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Herzig, Ivo; Paysan, Pascal; Scheib, Stefan; Züst, Alexander; Schilling, Frank-Peter; Montoya, Javier; Amirian, Mohammadreza; Stadelmann, Thilo; Eggenberger Hotz, Peter; Füchslin, Rudolf Marcel; Lichtensteiger, Lukas,
2022.
Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT [Poster].
In:
AAPM Annual Meeting, Washington, DC, USA, 10-14 July 2022.
American Association of Physicists in Medicine.
S. e325-e326.
Verfügbar unter: https://doi.org/10.1002/mp.15769
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Amirian, Mohammadreza; Montoya, Javier; Gruss, Jonathan; Stebler, Yves D.; Bozkir, Ahmet Selman; Calandri, Marco; Schwenker, Friedhelm; Stadelmann, Thilo,
2021.
In:
Proceedings of CISP-BMEI’21.
14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Shanghai, China, 23-25 October 2021.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Verfügbar unter: https://doi.org/10.21256/zhaw-23318
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Amirian, Mohammadreza; Tuggener, Lukas; Chavarriaga, Ricardo; Satyawan, Yvan Putra; Schilling, Frank-Peter; Schwenker, Friedhelm; Stadelmann, Thilo,
2021.
Two to trust : AutoML for safe modelling and interpretable deep learning for robustness [Paper].
In:
Postproceedings of the 1st TAILOR Workshop on Trustworthy AI at ECAI 2020.
1st TAILOR Workshop on Trustworthy AI at ECAI 2020, Santiago de Compostela, Spain, 29-30 August 2020.
Springer.
Verfügbar unter: https://doi.org/10.21256/zhaw-22061
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Glüge, Stefan; Amirian, Mohammadreza; Flumini, Dandolo; Stadelmann, Thilo,
2020.
How (not) to measure bias in face recognition networks [Paper].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, Hrsg.,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
Lecture Notes in Computer Science ; 12294.
Verfügbar unter: https://doi.org/10.1007/978-3-030-58309-5_10
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Tuggener, Lukas; Amirian, Mohammadreza; Rombach, Katharina; Lörwald, Stefan; Varlet, Anastasia; Westermann, Christian; Stadelmann, Thilo,
2019.
Automated machine learning in practice : state of the art and recent results [Paper].
In:
2019 6th Swiss Conference on Data Science (SDS).
6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019.
IEEE.
S. 31-36.
Verfügbar unter: https://doi.org/10.21256/zhaw-3156
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Stadelmann, Thilo; Amirian, Mohammadreza; Arabaci, Ismail; Arnold, Marek; Duivesteijn, Gilbert François; Elezi, Ismail; Geiger, Melanie; Lörwald, Stefan; Meier, Benjamin Bruno; Rombach, Katharina; Tuggener, Lukas,
2018.
Deep learning in the wild [Paper].
In:
Proceedings of the 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR).
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
IAPR.
Verfügbar unter: https://doi.org/10.21256/zhaw-3872
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Meier, Benjamin Bruno; Elezi, Ismail; Amirian, Mohammadreza; Dürr, Oliver; Stadelmann, Thilo,
2018.
Learning neural models for end-to-end clustering [Paper].
In:
Proceedings of the 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR).
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
IAPR.
Verfügbar unter: https://doi.org/10.21256/zhaw-3850
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Amirian, Mohammadreza; Schwenker, Friedhelm; Stadelmann, Thilo,
2018.
Trace and detect adversarial attacks on CNNs using feature response maps [Paper].
In:
Proceedings of the 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR).
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
IAPR.
Verfügbar unter: https://doi.org/10.21256/zhaw-3863
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Amirian, Mohammadreza; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter; Stadelmann, Thilo,
2019.
Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [Paper].
In:
ECML-PKDD 2019, Würzburg, Germany, 16-19 September 2019.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Verfügbar unter: https://doi.org/10.21256/zhaw-18357
Publikationen vor Tätigkeit an der ZHAW
Amirian, Mohammadreza; Kächele, Markus; Palm, Günther; Schwenker, Friedhelm. Support Vector Regression of Sparse Dictionary-based Features for View-Independent Action Unit Intensity Estimation. Facial Expression Recognition Challenge (FERA 2017).
Amirian, Mohammadreza; Kächele, Markus; Thiam, Patrik; Kessler, Viktor; Schwenker, Friedhelm. Continuous Multimodal Human Affect Estimation Using Echo State Networks. Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge (ACM 2016).
Amirian, Mohammadreza; Kächele, Markus; Schwenker, Friedhelm. Using Radial Basis Function Neural Networks for Continuous and Discrete Pain Estimation from Bio-physiological Signals. IAPR Workshop on Artificial Neural Networks in Pattern Recognition (2016).
Kächele, Markus; Thiam, Patrik; Amirian, Mohammadreza, Schwenker, Friedhelm; Palm, Günther. Methods for Person-Centered Continuous Pain Intensity Assessment from Bio-Physiological Channels. IEEE Journal of Selected Topics in Signal Processing (2016).
Kächele, Markus; Mohammadreza, Amirian; Thiam, Patrick; Werner, Philipp; Walter, Steffen; Palm, Günther; Schwenker, Friedhelm. "Adaptive Confidence Learning for the Personalization of Pain Intensity Estimation Systems." Evolving Systems.
Kazemi, Kamran; Amirian, Mohammadreza; Dehghani, Mohammad Javad. The S-transform Using a New Window to Improve Frequency and Time Resolutions. Signal, Image and Video Processing (2014).