Abstract
We present methods for processing the LBPs (local binary patterns) with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine). In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA). We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.
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