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Research on Image Reconstruction of Compressed Sensing Based on a Multi-Feature Residual Network
2020
Sensors
In order to solve the problem of how to quickly and accurately obtain crop images during crop growth monitoring, this paper proposes a deep compressed sensing image reconstruction method based on a multi-feature residual network. In this method, the initial reconstructed image obtained by linear mapping is input to a multi-feature residual reconstruction network, and multi-scale convolution is used to autonomously learn different features of the crop image to realize deep reconstruction of the
doi:10.3390/s20154202
pmid:32731604
fatcat:mu6ze6aibjfzvhkbrmaxttv3em