A small target recognition method, device and medium based on super-resolution reconstruction
A super-resolution reconstruction and super-resolution technology, applied in character and pattern recognition, instruments, biological models, etc., can solve problems such as poor performance, and achieve the effect of sufficient feature extraction, easy recognition, and improved recognition performance.
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Embodiment 1
[0029] A small target recognition method based on super-resolution reconstruction, such as figure 1 shown, including:
[0030] S1. Build a recognition model including a generator and a discriminator;
[0031] S2. Taking the low-resolution image as the input of the generator, taking the super-resolution image as the output of the generator, taking the real high-resolution image or the super-resolution image as the input of the discriminator, and The input of the discriminator is the probability of the real high-resolution image and the recognition result as the output of the discriminator; the recognition model is trained in combination with the generator loss function and the discriminator loss function; wherein, the generator loss function L G Expressed as: L G =L MSE +0.006×L VGG +0.001×L ADV +β×L CLS , where L MSE , L VGG , L ADV , L CLS are the pixel mean square error loss, VGG feature matching loss, confrontation loss, and target recognition loss, and β is the ...
Embodiment 2
[0072] A small target recognition device based on super-resolution reconstruction, including:
[0073] The model construction module is used to construct a recognition model including a generator and a discriminator; wherein, the low-resolution image is used as the input of the generator, the super-resolution image is used as the output of the generator, and the real high-resolution image is used as the output of the generator. The image or the super-resolution image is used as the input of the discriminator, and the probability that the input of the discriminator is a real high-resolution image and the recognition result are used as the output of the discriminator;
[0074] The model training module is used to initialize the network parameters of the generator and the discriminator, and train the recognition model in combination with the generator loss function and the discriminator loss function; wherein, the generator loss function L G Expressed as: L G = L MSE +0.006×L ...
Embodiment 3
[0079] The embodiment of the present application also provides a computer-readable storage medium. One or more non-transitory computer-readable storage media containing computer-executable instructions that, when executed by one or more processors, cause the processors to perform small super-resolution-based reconstruction Steps of the object recognition method.
[0080] A computer program product comprising instructions, when run on a computer, causes the computer to perform a super-resolution reconstruction-based small object recognition method.
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