ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning

31 January 2018

Papers citing "ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning"

9 / 9 papers shown

Title
A Deep Learning Approach to Block-based Compressed Sensing of Images A. Adler D. Boublil Michael Elad M. Zibulevsky 41 55 0 05 Jun 2016
Fully Convolutional Networks for Semantic Segmentation Evan Shelhamer Jonathan Long Trevor Darrell VOS SSeg 747 37,890 0 20 May 2016
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements K. Kulkarni Suhas Lohit Pavan Turaga Ronan Kerviche A. Ashok AI4TS 3DV 52 67 0 26 Jan 2016
Accurate Image Super-Resolution Using Very Deep Convolutional Networks Jiwon Kim Jung Kwon Lee Kyoung Mu Lee SupR 112 6,198 0 14 Nov 2015
A Deep Learning Approach to Structured Signal Recovery Ali Mousavi Ankit B. Patel Richard G. Baraniuk 56 443 0 17 Aug 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,595 0 01 Sep 2014
From Denoising to Compressed Sensing Christopher A. Metzler A. Maleki Richard G. Baraniuk 88 617 0 16 Jun 2014
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 289 26,217 0 11 Nov 2013