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- W3212422014 abstract "The biological signature recognition seems to be a solved problem, but when these systems are tested in the wild their accuracy collapsed abruptly. A case study of “Face Recognition Through Camera (FRTC)” was designed to make a state of art for biological signature recognition in the wild system with minimum data set required to provide the highest accuracy. The FRTC system was designed by integrating the best qualities of modern recognition systems present in recent times (OpenCV and Face API) to intensify the biological signature recognition in the wild. The case study FRTC would be tested with the classroom attendance without prior information to the students. It was expected that FRTC would be more accurate than OpenCV and Face API. The results have shown the FRTC is more accurate, 7.02% and -1% than OpenCV and Face API respectively." @default.
- W3212422014 created "2021-11-22" @default.
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- W3212422014 date "2021-07-06" @default.
- W3212422014 modified "2023-10-13" @default.
- W3212422014 title "Intensified Biological Signature Recognition in the Wild: A Case Study" @default.
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- W3212422014 doi "https://doi.org/10.1109/icccnt51525.2021.9579578" @default.
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