|
|
|
Maxim Bakaev, Sebastian Heil and Martin Gaedke
Training data for user behavior models that predict subjective dimensions of visual perception are often too scarce for deep learning methods to be applicable. With the typical datasets in HCI limited to thousands or even hundreds of records, feature-bas...
ver más
|
|
|
|
|
|
|
Alexey Kozin, Anton Gerasimov, Maxim Bakaev, Anton Pashkov and Olga Razumnikova
Brain?computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) are inexpensive and do not require user training. However, the highly personalized reaction to visual stimulation is an obstacle to the wider application of this t...
ver más
|
|
|
|
|
|
|
Alina Epanchintseva,Maxim Bakaev
Pág. 4 - 10
Today's international sport is a competition of fast managerial decisions, high technology and strong investments. Correspondingly, rational selection of capable sportsmen is crucial for optimal allocation of the limited training resources. In our paper,...
ver más
|
|
|
|
|
|
|
Maxim Bakaev and Olga Razumnikova
Tasks that imply engagement of visual-spatial working memory (VSWM) are common in interaction with two-dimensional graphical user interfaces. In our paper, we consider two groups of factors as predictors of user performance in such tasks: (1) the metrics...
ver más
|
|
|
|