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- W3080497579 abstract "Quick Response (QR) Code plays an important role in connecting the physical world where we live in and the digital world that contains information. However, the pictures made up of black and white color blocks really affect people's moods. This paper designs a visual appealing two-dimensional code to help people access information from offline to online. A Deep Neural Network (DNN) based encoder hides information into natural images and a DNN based decoder recovers it. A novel finder pattern is designed to help the decoding device to locate our codes quickly. We design a decoding device. It consists of an AI chip, camera, and LCD screen. The information is invisible in our generated hidden images but detectable by our device. With the help of powerful edge computing, the device can recover the hidden information from the pictures in real time." @default.
- W3080497579 created "2020-09-01" @default.
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- W3080497579 date "2020-08-01" @default.
- W3080497579 modified "2023-10-16" @default.
- W3080497579 title "Real time Robust Invisible Hyperlinks in Physical Photographs Based on Embodied AI Platform" @default.
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- W3080497579 doi "https://doi.org/10.1109/mipr49039.2020.00063" @default.
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