Face recognition architecture design method based on edge calculation and cloud overall planning
A face recognition and architecture design technology, applied in computing, computer components, neural learning methods, etc., can solve problems such as data transmission and deep model training, and achieve fast response time, high accuracy, and improved accuracy.
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[0048] The technology of network architecture design in this embodiment mainly involves the following types of technologies: 1) Edge computing technology: use edge computing technology to make task response close to the data front end, reducing response delay; 2) cloud-based face recognition architecture: joint The local models of multiple edge nodes can train the joint model by constructing an autoencoder to improve the recognition accuracy.
[0049] The network architecture design is based on the TensorFlow framework and the Pycharm development environment: the TensorFlow framework is a development framework based on the python language, which can easily and quickly build a reasonable deep learning network, and has good cross-platform interaction capabilities. TensorFlow provides many encapsulation functions in the deep learning architecture and interfaces of various image processing functions, including OpenCV-related image processing functions. The TensorFlow framework can...
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