This article describes a vision system that uses deep learning to recognize 24 static signs of the American Sign Alphabet in real time. As part of the project, images of signs from four publicly available databases were used as a training set. A DenseNet was implemented for image recognition. For testing, images were acquired with the use of a web camera. The accuracy of sign recognition in images is more than 80. The real-time version of the system was implemented.
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