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Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator
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作者 Summra Saleem M.Usman Ghani Khan +3 位作者 Tanzila Saba Ibrahim Abunadi Amjad Rehman Saeed Ali Bahaj 《Computers, Materials & Continua》 SCIE EI 2022年第1期505-521,共17页
Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal identification.In Edge GAN,the major contribution is attribu... Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal identification.In Edge GAN,the major contribution is attribute guided vector that enables high visual quality content generation.This research study proposes automatic face image realism from freehand sketches based on Edge GAN.We propose a density variant image synthesis model,allowing the input sketch to encompass face features with minute details.The density level is projected into non-latent space,having a linear controlled function parameter.This assists the user to appropriately devise the variant densities of facial sketches and image synthesis.Composite data set of Large Scale CelebFaces Attributes(ClebA),Labelled Faces in theWild(LFWH),Chinese University of Hong Kong(CHUK),and self-generated Asian images are used to evaluate the proposed approach.The solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation. 展开更多
关键词 Edge generator density variant sketch generator face translation recognition residual block
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