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- W4300624980 abstract "With the development of modern computer technology and artificial intelligence, face image processing technology has been widely used in people's life and work. In order to realise face image detection and recognition in dynamic video, this paper proposes a face detection and recognition technology based on MTCNN algorithm. MTCNN algorithm includes R-Net, O-net and P-net deep network models, which can realise face image deep processing in dynamic video. In order to train MTCNN algorithm deeply, Wider_Face and CelebA database training sets were used to train the additional test tasks and regression key points of the model. After setting the main parameters of MTCNN algorithm, the algorithm is simulated and analysed. Through the comparative simulation analysis of traditional algorithm, SVM algorithm and 2DPCA algorithm, it can be seen that MTCNN algorithm has more excellent performance and can meet the needs of face image detection and recognition in dynamic video." @default.
- W4300624980 created "2022-10-03" @default.
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- W4300624980 date "2022-01-01" @default.
- W4300624980 modified "2023-09-30" @default.
- W4300624980 title "Research on video image face detection and recognition technology based on improved MTCNN algorithm" @default.
- W4300624980 doi "https://doi.org/10.1504/ijwmc.2022.124811" @default.
- W4300624980 hasPublicationYear "2022" @default.
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