Pattern Recognition Company GmbH
Institut für Neuro- und Bioinformatik, Universität zu Lübeck
2015 – Current time: PhD in Computer Science, Lübeck, Germany
2013 – 2015: Master degree in Computer Science, Trento, Italy
2007 – 2013: Bachelor degree in Software Engineering, Minsk, Belarus.
Pattern Recognition, Machine Learning, Deep Neural Networks
- Activity Recognition with Recurrent Neural Networks / S. Semeniuta // Thesis
- Facial Expression Recognition under a Wide Range of Head Poses / R. L. Vieriu, S. Tulyakov, S. Semeniuta, E. Sangineto, N. Sebe // FG 2015, Ljubljana, Slovenia.
- Robust Real-Time Extreme Head Pose Estimation / S. Tulyakov, R. L. Vieriu, S. Semeniuta, N. Sebe //
ICPR 2014, Stockholm, Sweden.
This research project is focused on attempting to model human visual perception from an algorithmic and computational point of view. The computational model researched in this project is based on the machine-learning field called Deep Learning. The main algorithm in this field is the Artificial Neural Network (ANN). It is a model that is inspired by structure of the brain, i.e. a huge number of relatively simple units, neurons, and connections between them.