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In this paper we develop a novel computational sensing framework for sensing and recovering structured signals.
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“Reconnet: Non-iterative reconstruction of images from compressively sensed random measurements,”
K. Kulkarni, S. Lohit, P. Turaga, R. Kerviche, and A. Ashok, · 2016
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“Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network,”
W. Shi, J. Caballero, F. Huszár, J. Totz, A. P Aitken, R. Bishop, D. Rueckert, and Z. Wang, · 2016
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“Learning to invert: Signal recovery via deep convolutional networks,”
A. Mousavi and R. G. Baraniuk, · 2017
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