Sensor sensing image recognition method, system and device and storage medium

Abstract

The invention discloses a sensor sensing image recognition method, system and device and a storage medium, and the method comprises the steps: obtaining first array data of a sensor sensing image, and adding Gaussian noise to the first array data to obtain second array data; performing function relation conversion on the second array data to obtain a pixel capacitor array, and inputting the pixel capacitor array into a pre-trained convolutional neural network; performing convolution calculation on the pixel capacitor array through a convolution layer of the convolutional neural network to obtain a sensor charge quantity array; performing data scaling on the sensor charge quantity array to obtain third array data, and extracting data feature information of the third array data through an activation function of the convolutional neural network; and inputting the data feature information into a full connection layer of the convolutional neural network, calculating to obtain an output vector, and determining a recognition result of the sensor sensing image according to the output vector. The method improves the recognition efficiency of the sensor sensing image, and can be widely applied to the technical field of artificial intelligence.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a sensor sensing image recognition method, system, device and storage medium. Background technique [0002] At present, the commonly used edge capacitive pixel array sensors, such as fingerprint sensors, etc., use capacitive pixels to generate parasitic capacitance under external perception to change the capacitance value, and then use the measurement circuit to measure the changed capacitance value and convert it into a digital value, and then Handed over to the processor, the processor classifies the digital data representing the capacitance value information obtained by each capacitor pixel to calculate the recognition result. This process does not make full use of the electrical characteristics of the capacitor and the physical laws of the circuit structure. Large storage space and high computing power are required, and a large amount of computing time is cons...

AI Technical Summary

Problems solved by technology

[0002] At present, the commonly used edge capacitive pixel array sensors, such as fingerprint sensors, etc., use capacitive pixels to generate parasitic capacitance under external perception to change the capacitance value, and then use the measurement circuit to measure the changed capacitance value and convert it into a digital value, and then Handed over to the processor, the processor classifies the digital data representing the capacitance value information obtained by each capacitor pixel to calculate the recognition result. This process does not make full use of the electrical characteristics of the capacitor and the physical laws of the circuit structure. Requires large storage space and high computing power, and consumes a lot of computing time in the recognition process, which affects the recognition efficiency of sensor-sensed images

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