DOI 10.17586/0021-3454-2023-66-3-247-250
UDC 612.82; 159.931; 004.93
AUTOMATIC RECOGNITION OF VISUAL STIMULES BY SINGLE EVOKED POTENTIALS ON AN ELECTROENCEPHALOGRAM
ITMO University, Saint Petersburg, 197101, Russian Federation; Professor, Scientific Secretary
I. V. Burdaev
ITMO University, Faculty of Software Engineering and Computer Systems;
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Abstract. The necessity of increasing the efficiency of automatic classification of visual stimuli by single evoked potentials on the observer's electroencephalogram is substantiated. The factors affecting the accuracy of recognition of the type of presented visual stimuli (living/non-living, clear/blurred) are determined. A data processing algorithm is developed that makes it possible to identify significant differences in the amplitudes of single evoked potentials.
Keywords: recognition of single evoked potentials, deep learning methods, artificial neural networks
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