Compressive-Sensing Data Reconstruction for Structural Health
Monitoring: A Machine-Learning Approach

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Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach

7 January 2019

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Papers citing "Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach"

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Title
Recurrent Inference Machines for Solving Inverse Problems P. Putzky Max Welling AI4CE 53 127 0 13 Jun 2017
Solving ill-posed inverse problems using iterative deep neural networks J. Adler Ozan Oktem 85 617 0 13 Apr 2017
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models Jen-Hao Rick Chang Chun-Liang Li Barnabás Póczós B. Kumar Aswin C. Sankaranarayanan 63 348 0 29 Mar 2017
Deep Convolutional Neural Network for Inverse Problems in Imaging Kyong Hwan Jin Michael T. McCann Emmanuel Froustey M. Unser 71 2,122 0 11 Nov 2016
Colorful Image Colorization Richard Y. Zhang Phillip Isola Alexei A. Efros 149 3,532 0 28 Mar 2016
Learning Representations for Automatic Colorization Gustav Larsson Michael Maire Gregory Shakhnarovich VLM SSL 94 1,014 0 22 Mar 2016
Super-Resolution with Deep Convolutional Sufficient Statistics Joan Bruna Pablo Sprechmann Yann LeCun SupR 65 326 0 18 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures J. Hershey Jonathan Le Roux F. Weninger BDL 118 432 0 09 Sep 2014