Computer Vision, Perception and Cognition Group
“AI is THE key technology of the digital transformation, across sectors and industries, with major effects on our societies. Our research thus makes major contributions to the development of robust and trustworthy AI methods, and we enthusiastically teach their safe implementation and application.”
- Pattern recognition with deep learning
- Machine perception, computer vision and speaker recognition
- Neural system development
The CVPC group conducts pattern recognition research, working on a wide variety of tasks relating to image, audio, and signal data per se. We focus on deep neural network and reinforcement learning methodology, inspired by biological learning. Each task we study has its own learning target (e.g., detection, classification, clustering, segmentation, novelty detection, control) and corresponding use case (e.g., predictive maintenance, speaker recognition for multimedia indexing, document analysis, optical music recognition, computer vision for industrial quality control, automated machine learning, deep reinforcement learning for automated game play or building control), which in turn sheds light on different aspects of the learning process. We use this experience to create increasingly general AI systems built on neural architectures.
- Insight: keynotes, trainings
- AI consultancy: workshops, expert support, advise, technology assessment
- Research and development: small to large-scale collaborative projects, third party-funded research, student projects, commercially applicable prototypes
The aim of this project is to develop a demonstrator in the form of an Android app, which can visualize the speeches of two interlocutors in real time. This should enable a superior to recognize, for example, whether he or she talks too much in an employee appraisal interview or whether the interview is balanced.In ...
Proceedings of the 7th SDS.
7th Swiss Conference on Data Science, Lucerne, Switzerland, 26 June 2020.
Available from: https://doi.org/10.21256/zhaw-19978
Aydarkhanov, Ruslan; Ušćumlić, Marija; Chavarriaga, Ricardo; Gheorghe, Lucian; del R Millán, José,
Journal of Neural Engineering.
17(3), pp. 036030.
Available from: https://doi.org/10.1088/1741-2552/ab95eb
Orset, Bastien; Lee, Kyuhwa; Chavarriaga, Ricardo; Millan, Jose del R.,
IEEE Transactions on Biomedical Engineering.
68(1), pp. 3-10.
Available from: https://doi.org/10.1109/TBME.2020.3001981
Iturrate, Iñaki; Chavarriaga, Ricardo; Millán, José del R.,
Millan, José del R; Ramsay, Nick F., eds.,
Handbook of Clinical Neurology ; 168.
Available from: https://doi.org/10.1016/B978-0-444-63934-9.00023-8
Jeunet, Camille; Tonin, Luca; Albert, Louis; Chavarriaga, Ricardo; Bideau, Benoît; Argelaguet, Ferran; Millán, José del R.; Lécuyer, Anatole; Kulpa, Richard,
Available from: https://doi.org/10.1038/s41598-020-58533-2