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Machine Learning Method for Functional Assessment of Retinal Models
Challenges in the field of retinal prostheses motivate the development of retinal models to accurately simulate Retinal Ganglion Cells (RGCs) responses.
A theoretical look at ordinal classification methods based on reference sets composed of characteristic actions
From a theoretical view, this paper addresses the general problem of designing ordinal classification methods based on comparing actions with subset of actions, which are representative of their classes (categories).
a theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes
Each of them is composed of two complementary assignment procedures, which correspond through the transposition operation and should be used conjointly.
A new model for the implementation of positive and negative emotion recognition
Lastly, QDA and KNN classifiers and population rating criterion for stimuli labeling have been suggested as the most suitable approaches for EEG-base emotion recognition.
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