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A signal processing interpretation of noise-reduction convolutional
  neural networks

A signal processing interpretation of noise-reduction convolutional neural networks

25 July 2023
Luis A. Zavala-Mondragón
Peter H. N. de With
Fons van der Sommen
ArXiv (abs)PDFHTML

Papers citing "A signal processing interpretation of noise-reduction convolutional neural networks"

13 / 13 papers shown
Title
Plug-and-Play Image Restoration with Deep Denoiser Prior
Plug-and-Play Image Restoration with Deep Denoiser Prior
Peng Sun
Yawei Li
W. Zuo
Lei Zhang
Luc Van Gool
Radu Timofte
DiffMSupR
101
807
0
31 Aug 2020
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
102
1,022
0
22 Dec 2019
Deep K-SVD Denoising
Deep K-SVD Denoising
M. Scetbon
Michael Elad
P. Milanfar
SupR
81
108
0
28 Sep 2019
Momentum-Net: Fast and convergent iterative neural network for inverse
  problems
Momentum-Net: Fast and convergent iterative neural network for inverse problems
Il Yong Chun
Zhengyu Huang
Hongki Lim
Jeffrey A. Fessler
104
82
0
26 Jul 2019
Robust and interpretable blind image denoising via bias-free
  convolutional neural networks
Robust and interpretable blind image denoising via bias-free convolutional neural networks
S. Mohan
Zahra Kadkhodaie
Eero P. Simoncelli
C. Fernandez‐Granda
AI4CE
74
125
0
13 Jun 2019
Nonlinear Approximation and (Deep) ReLU Networks
Nonlinear Approximation and (Deep) ReLU Networks
Ingrid Daubechies
Ronald A. DeVore
S. Foucart
Boris Hanin
G. Petrova
100
142
0
05 May 2019
Understanding Geometry of Encoder-Decoder CNNs
Understanding Geometry of Encoder-Decoder CNNs
J. C. Ye
Woon Kyoung Sung
3DVAI4CE
69
73
0
22 Jan 2019
Multi-level Wavelet-CNN for Image Restoration
Multi-level Wavelet-CNN for Image Restoration
Pengju Liu
Hongzhi Zhang
Peng Sun
Liang Lin
W. Zuo
SupR
65
651
0
18 May 2018
A Review of Convolutional Neural Networks for Inverse Problems in
  Imaging
A Review of Convolutional Neural Networks for Inverse Problems in Imaging
Michael T. McCann
Kyong Hwan Jin
M. Unser
3DV
61
593
0
11 Oct 2017
Framing U-Net via Deep Convolutional Framelets: Application to
  Sparse-view CT
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-view CT
Yoseob Han
J. C. Ye
72
519
0
28 Aug 2017
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network
  (RED-CNN)
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
Hu Chen
Yi Zhang
Mannudeep K. Kalra
Feng Lin
Yang Chen
Peixi Liao
Jiliu Zhou
Ge Wang
MedIm
109
1,311
0
01 Feb 2017
Deep Convolutional Neural Network for Inverse Problems in Imaging
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
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
457
7,666
0
03 Jul 2012
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