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The paper deals with the classification of Czech sign language single hand alphabet letters from static images using convolutional neural network (CNN). Proposed CNN architecture exhibits about 71 % successful rate of classifying the letters signed by the person not included in the training data set.

CLASSIFICATION OF CZECH SIGN LANGUAGE ALPHABET LETTERS USING CNN – PRELIMINARY STUDY