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We are interested in enabling natural human-computer interaction by combining techniques from machine learning, computer vision, computer graphics, human-computer interaction and psychology. Specific areas that we focus on include: multimodal human-computer interfaces, affective computing, pen-based interfaces, sketch-based applications, intelligent user interfaces, applications of computer vision and machine learning to solving real world problems. Browse through the publications and research pages to get a flavor of IUI@Koc.

New Publication in Computer Physics Communications
Sezgin&Sezgin‘s article on finding portable congruential random number generators has been accepted for publication in the Computer Physics Communications journal. 
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DPFrag: Trainable Stroke Fragmentation Based on Dynamic Programming
Many computer graphics applications must fragment freehand curves into sets of prespecified geometric primitives. For example, sketch recognition typically converts
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