Compressed object imaging method and system based on deep learning
A technology of deep learning and imaging methods, applied in image coding, image data processing, instruments, etc., can solve the problems of information transmission speed and information processing speed limit, restrict development, and affect the real-time performance of the system, so as to improve real-time performance and solve problems. Storage and transmission problems, the effect of saving network bandwidth and storage overhead
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[0041] see figure 1Part1 and Part3, which are the deep learning network structure diagram based on the group full convolutional neural network of the embodiment of the present invention.
[0042] In this deep learning network, Part1 is the input of the image and the feature measurement matrix part of the extracted target object. The arrow with the word CS Layer indicates the convolutional layer designed according to the theory of compressed sensing. After the network training is completed, the convolutional layer’s The parameters will be used as the feature measurement matrix in the compressed sensing theory to achieve efficient measurement of specific target objects. The size and number of filters used as the first convolutional layer are manually adjusted according to the needs of samples and compression rates, which are hyperparameters. Part3 is the reconstructed sub-network of the target object and the output part of the image. The arrows with the words conv0, conv1, conv...
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