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• W2890147496 abstract "Aiming at the problems of image super-resolution algorithm with many convolutional neural networks, such as large parameters, large computational complexity and blurred image texture, we propose a new algorithm model. The classical convolutional neural network is improved, the convolution kernel size is adjusted, and the parameters are reduced; the pooling layer is added to reduce the dimension. Reduced computational complexity, increased learning rate, and reduced training time. The iterative back-projection algorithm is combined with the convolutional neural network to create a new algorithm model. The experimental results show that compared with the traditional facial illusion method, the proposed method can obtain better performance." @default.
• W2890147496 created "2018-09-27" @default.
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• W2890147496 date "2018-01-01" @default.
• W2890147496 modified "2023-10-01" @default.
• W2890147496 title "Human Face Super-Resolution Based on Hybrid Algorithm" @default.
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• W2890147496 doi "https://doi.org/10.4236/ami.2018.84004" @default.
• W2890147496 hasPublicationYear "2018" @default.
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