Face recognition reminding system based on convolutional neural network

Abstract

The invention discloses a face recognition reminding system based on a convolutional neural network. The system comprises a raspberry pi control module, a voice output module and a video acquisition module. The raspberry Pi control module is connected with a camera of the video acquisition module through a CSI port. Starting and working of the camera are controlled by the CSI port. The raspberry Pi control module is connected with a control pin and a power supply pin of the voice output module through a voice output control signal port and a power supply port of GPIO. According to the invention, the convolutional neural network is adopted to carry out face recognition and prompt, the face detection is not influenced by the position of the face, and the recognition accuracy is good.

Description

technical field [0001] The invention relates to the technical field of convolutional neural network and face recognition, in particular to a face recognition reminder system based on convolutional neural network. Background technique [0002] In recent years, with the rapid development of image processing and machine learning technology and the continuous updating of computer hardware equipment, deep learning based on convolutional neural networks has made remarkable progress in the fields of computer vision, image classification, speech recognition, and natural language processing. This also makes it possible to apply face recognition technology based on convolutional networks to reminder systems. At the same time, such a design will bring the advantages of convolutional neural networks such as robustness, accuracy and flexibility into the reminder system, so that the system can operate stably in the face of complex environments. [0003] Among the approximate technical so...

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Problems solved by technology

[0003] Among the approximate technical solutions, the existing reminder systems mostly adopt design solutions based on sensor technology, such as infrared induction and electromagnetic induction technology, etc. At present, there is no design scheme that combines convolutional neural network technology with embedded reminder systems

In the traditional face recognition technology, there is a recognition method using eigenvalue matching, but this has higher requirements for the deformation, light and shade, occlusion and other conditions of the face image, and is worse than the convolutional neural network in terms of anti-interference ability. , so traditional face recognition technology is difficult to design a reminder system suitable for various situations

[0004] In addition, the existing reminder system is not very flexible. Regardless of whether people enter or go out, or other creatures or objects pass by, as long as the trigger conditions are met, the system will remind, which is easy to cause trouble in some occasions.

In addition, existing identification reminder systems such as infrared sensor reminder systems are powered by batteries, once the power is exhausted, it will lead to unpredictable consequences

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