Learning to invert: Signal recovery via Deep Convolutional Networks (original) (raw)

Fast Reconstruction of 1D Compressive Sensing Data Using a Deep Neural Network

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International Journal of Signal Processing Systems, 2020

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Error Resilient Deep Compressive Sensing

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The 11th International Symposium on Information and Communication Technology

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ArXiv, 2017

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Fully Learnable Model for Task-Driven Image Compressed Sensing

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2021

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DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks

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2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2017

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Sparse representation using compressed sensing via deep learning

Safish Mary

2020

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Distributed Compressive Sensing: A Deep Learning Approach

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Learned D-AMP: Principled Neural Network based Compressive Image Recovery

Ali Mousavi

2017

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MsDC-DEQ-Net: Deep Equilibrium Model (DEQ) with Multi-scale Dilated Convolution for Image Compressive Sensing (CS)

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arXiv (Cornell University), 2024

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Effective Image Reconstruction Using Various Compressed Sensing Techniques

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Multi-Scale Deep Compressive Imaging

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IEEE Transactions on Computational Imaging, 2021

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A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery

Ali Mousavi

2019

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Dual-Path Image Reconstruction: Bridging Vision Transformer and Perceptual Compressive Sensing Networks

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Computer Science and Information Systems (FedCSIS), 2019 Federated Conference on, 2023

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AMPA-Net: Optimization-Inspired Attention Neural Network for Deep Compressed Sensing

Charles Zhou

2020 IEEE 20th International Conference on Communication Technology (ICCT), 2020

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A deep error correction network for compressed sensing MRI

Salik Hussain

BMC Biomedical Engineering, 2020

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Making sense of randomness: Fast signal recovery from compressive samples

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2016 24th European Signal Processing Conference (EUSIPCO), 2016

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Compressive Domain Deep CNN for Image Classification and Performance Improvement Using Genetic Algorithm-Based Sensing Mask Learning

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Applied Sciences

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End-to-End Video Compressive Sensing Using Anderson-Accelerated Unrolled Networks

Ryan Ortega

2020 IEEE International Conference on Computational Photography (ICCP), 2020

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Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems

Mário Figueiredo

2007

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Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operation

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arXiv (Cornell University), 2021

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Solving Inverse Computational Imaging Problems using Deep Pixel-level Prior

Akshat Dave

IEEE Transactions on Computational Imaging, 2018

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Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operation_supp1-3318946.pdf

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Signal reconstruction via compressive sensing

Sonja Grgic

Proceedings Elmar 2011, 2011

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MC-ISTA-Net: Adaptive Measurement and Initialization and Channel Attention Optimization inspired Neural Network for Compressive Sensing

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ArXiv, 2019

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A Study on Compressive Sensing and Reconstruction Approach

utsav bhatt

Journal of emerging technologies and innovative research, 2015

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Convolutional neural networks analysed via inverse problem theory and sparse representations

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IET Signal Processing

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A Learning-Based Framework for Quantized Compressed Sensing

karimi mahabadi

IEEE Signal Processing Letters

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Compressive sensing reconstruction via decomposition

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Signal Processing-image Communication, 2016

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SALSA-Net: Explainable Deep Unrolling Networks for Compressed Sensing

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A Survey of Compressive Sensing Based Greedy Pursuit Reconstruction Algorithms

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Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss

S R Nirmala

IEEE transactions on medical imaging, 2018

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Sparsity-Aware Learning and Compressed Sensing: An Overview

Sergios Theodoridis

Academic Press Library in Signal Processing, 2014

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Compressive image recovery using recurrent generative model

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2017 IEEE International Conference on Image Processing (ICIP), 2017

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Reconstruction Of Sparse Signals Using Likelihood Maximization from Compressive Measurements with Gaussian And Saturation Noise

Shuvayan Banerjee

2021 29th European Signal Processing Conference (EUSIPCO)

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Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing

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IEEE Transactions on Neural Networks and Learning Systems, 2021

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