16 citations · 22 across the 7 of their papers we have counts for
7 papers · 1 filter
Blink Rate Variability during resting and reading sessions
Artem Lenskiy, Rafal Paprocki
It has been shown that blinks occur not only to moisturize eyes and as a defensive response to the environment, but are also caused by mental processes. In this paper, we investiga…
Machine Learning for Visual Navigation of Unmanned Ground Vehicles
Artem A. Lenskiy, Jong-Soo Lee
The use of visual information for the navigation of unmanned ground vehicles in a cross-country environment recently received great attention. However, until now, the use of textur…
Image segmentation of cross-country scenes captured in IR spectrum
Artem Lenskiy
Computer vision has become a major source of information for autonomous navigation of robots of various types, self-driving cars, military robots and mars/lunar rovers are some exa…
Extracting Blink Rate Variability from EEG Signals
Rafal Paprocki, Temesgen Gebrehiwot, Marija Gradinscak +1
Generally, blinks are treated on equal with artifacts and noise while analyzing EEG signals. However, blinks carry important information about mental processes and thus it is impor…
Analysis of Blink Rate Variability during reading and memory testing
Temesgen Gebrehiwot, Rafal Paprocki, Artem Lenskiy
In this paper we investigated how statistical properties of the blink rate variability changes during two mental tasks: reading a passage and memory testing. To construct time seri…
A movie genre prediction based on Multivariate Bernoulli model and genre correlations
Eric Makita, Artem Lenskiy
Movie ratings play an important role both in determining the likelihood of a potential viewer to watch the movie and in reflecting the current viewer satisfaction with the movie. T…
A multinomial probabilistic model for movie genre predictions
Eric Makita, Artem Lenskiy
This paper proposes a movie genre-prediction based on multinomial probability model. To the best of our knowledge, this problem has not been addressed yet in the field of recommend…