Facial expression is a basic way to express human emotions, and it is the primary medium for individuals to communicate with others. The display of facial expressions can better understand the other person's feelings and emotions. With the continuous development of artificial intelligence technology, the demand for human-computer interaction has also increased. The development of artificial intelligence plays an important role in face recognition and micro-expression changes when users watch IPTV. Because of the small range of motion and fast change of micro-expression, it is difficult to analyze it manually. Therefore, it is very necessary to develop a reliable recognition system. In this paper, the face recognition model facenet model is used to learn the image features of the face, Yolov5 and Yolox neural network are used as the basis to compare the models trained, and the performance of the selected model is tested to select the best effect.
The relationship between modern education development and artificial intelligence is getting closer and closer, but the technology of online examination and test detection needs to be improved. Most of the existing technologies are aimed at the comparison of pictures per frame, head detection, limb detection, key part detection, etc., although this effect is ideal, but at the same time the requirements for conditions are high. In this paper, for online exam detection, it is proposed to use face recognition and Euclidean distance combined with Yolov3 to complete the cheating detection.
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