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- W4385192612 abstract "A difficult machine vision challenge is predicting qualities from real-world facial photos. Traditionally, 3 technological blocks—face location, facial description creation, and attribute classification—must be cascaded in a process in order to automatically characterize face attributes from images that include faces. The variety of the definable face characteristics being acknowledged, our facial descriptor, which are built from several layers of the CNNs for various characteristics in recognition of the diversity of the describable face qualities, are designed to make face attribute prediction as simple as possible. In-depth comparisons between our method and the state-of-the-art are demonstrated through experiments on the two significant datasets LFWA and CelebA. Our research not only presents a successful method for predicting a facial characteristic, but it also raises a crucial issue of how to best apply the capabilities of pre-built CNN models to new applications" @default.
- W4385192612 created "2023-07-25" @default.
- W4385192612 creator A5041200377 @default.
- W4385192612 creator A5061051432 @default.
- W4385192612 date "2023-05-12" @default.
- W4385192612 modified "2023-09-23" @default.
- W4385192612 title "Estimation of Face Attributes Using Standard CNN Features" @default.
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- W4385192612 doi "https://doi.org/10.1109/icacite57410.2023.10183194" @default.
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