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Face Recognition based on Frontalization of Multiple Poses and Expressions using GGAN and PCA
Face identification is an essential application in recent times as it has several applications like surveillance, criminal identification, etc. Many face recognition methods are still facing various challenges by researchers in real-time applications because of multiple rotational angles of faces and different expressions. To overcome this issue, we come up with the novel approach of Global Generative Adversarial Networks (G-GAN) to convert various expressions and side images into frontaldoi:10.37896/ymer21.06/11 fatcat:dwtku6m5ajh7flspiclk4ryly4