Therefore, the purpose of the work is to find and optimize the most satisfactory in terms of accuracy algorithm for classifying human emotions based on facial images. Technologies for recognizing companies to improve customer service use human emotions make decisions about interviewing candidates and optimize the emotional impact of advertising. However, the human face has the greatest expressiveness. They can be expressed in different ways: facial expressions, posture, motor reactions, voice. The work examines emotions as a special type of mental processes that express a person’s experience of his attitude to the surrounding world and himself. The subject of research in the article is the software implementation of a neural image classifier.
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