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Single-photon compression recognition system based on binary neural network and using method thereof

A binary neural and identification system technology, applied in the field of single-photon compression identification system, can solve the problems of low identification accuracy, complex scheme, long time-consuming, etc., and achieve the effect of high identification accuracy and fast speed.

Inactive Publication Date: 2021-02-09
NANCHANG UNIV
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Problems solved by technology

However, the recognition of this type of method requires image reconstruction of the target first, so there are disadvantages such as complex scheme, long time consumption and low recognition accuracy at extremely low sampling rate

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  • Single-photon compression recognition system based on binary neural network and using method thereof
  • Single-photon compression recognition system based on binary neural network and using method thereof
  • Single-photon compression recognition system based on binary neural network and using method thereof

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Embodiment Construction

[0029] The present invention will be further described below in conjunction with drawings and embodiments.

[0030] Such as figure 1 Shown is the neural network (BFCI-Net) of the present invention (the single-photon compression recognition system based on binary neural network), which reshape the picture into a column of vectors, and then input it to the binary neural network for training. The first layer is a binary fully connected layer with weight matrix size (x, y), the size of x depends on the size of the picture, and the size of y depends on the sampling rate MR of compressed sensing, that is, y=MR*x , the weight matrix obtained through training is the measurement matrix of compressed sensing. After several layers of fully connected layers and batch normalization layers, the prediction results of the pictures are output from the output layer.

[0031] 1.1 Compressed sampling subnetwork F c (·)

[0032] The first fully connected layer in the neural network (BFCI-Net) ...

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Abstract

The invention belongs to the technical field of single photon imaging, and particularly relates to a single-photon compression identification system based on a binary neural network and a using methodthereof, the single photon compression identification system comprises a binary compression sampling sub-network and an identification sub-network, a weight matrix of the binary compression samplingsub-network is a binary matrix composed of + 1 and 1, and the binary compression sampling sub-network is a binary matrix composed of + 1 and 1. The '+ 1' and the '1' are respectively used for modulating forward turning and reverse turning of a DMD micromirror in the single-pixel imaging system; the identification sub-network is used for carrying out dimension compression and expansion on the measurement value matrix and completing category identification to obtain an identification result, and the weight of the identification sub-network is obtained by network training. According to the invention, the identification speed is faster; the invention can complete the recognition of images without image reconstruction, is higher in recognition accuracy, and can maintain the higher recognition accuracy under the condition of extremely low sampling rate.

Description

technical field [0001] The invention belongs to the technical field of single-photon imaging, and in particular relates to a binary neural network-based single-photon compression recognition system and an application method thereof. Background technique [0002] Single-pixel imaging is an imaging method that uses a single-point detector to capture a two-dimensional image. In 2008, Romber and Baraniuk of Rice University proposed a single-pixel camera scheme based on the principle of compressed sensing. This scheme uses Spatial sparsity of images and point detectors enable imaging of 2D objects. In 2012, Yu Wenkai of the Chinese Academy of Sciences combined single-pixel photography technology with photon counting imaging technology to realize ultra-high-sensitivity photon counting imaging that broke through the limit of the detector itself. This imaging solution has the advantages of high sensitivity and low photon level. [0003] With the development of computer vision techn...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/42G06N3/04G06N3/08G02B26/08
CPCG06N3/04G06N3/08G02B26/0833G06V30/32G06V10/32G06F18/00
Inventor 鄢秋荣祝志太熊乙宁蔡源鹏杨耀铭
Owner NANCHANG UNIV
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