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Mohammadreza Amirian

  Mohammadreza Amirian

Mohammadreza Amirian

ZHAW School of Engineering
Forschungsschwerpunkt Information Engineering
Obere Kirchgasse 2 / Steinberggasse 12/14
8400 Winterthur

+41 (0) 58 934 47 62

Personal profile

Position at the ZHAW

Research Assistant

Expertise and research interests

Machine Learning, Pattern Recognition, Neural Networks, Affective Computing,Facial Expression Estimation, Computer Vision, Digital Signal Processing, Bio-physiological Signal Processing, Pain Estimation, Sonar, Image Processing, Compressed Sensing, Medical Imaging, Multi-modal Data Fusion, Recurrent Networks

Current research: Deep Learning and image processing

Educational background

Maseter, Comuunications Technology, 2017, Ulm University

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Book parts, peer-reviewed
Conference contributions, peer-reviewed
Other publications
Publications before appointment at the 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).