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Interpolation and Denoising of Seismic Data using Convolutional Neural
  Networks
v1v2v3v4 (latest)

Interpolation and Denoising of Seismic Data using Convolutional Neural Networks

23 January 2019
S. Mandelli
V. Lipari
Paolo Bestagini
Stefano Tubaro
ArXiv (abs)PDFHTML

Papers citing "Interpolation and Denoising of Seismic Data using Convolutional Neural Networks"

7 / 7 papers shown
Title
Image Inpainting for Irregular Holes Using Partial Convolutions
Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu
F. Reda
Kevin J. Shih
Ting-Chun Wang
Andrew Tao
Bryan Catanzaro
209
1,931
0
20 Apr 2018
Shift-Net: Image Inpainting via Deep Feature Rearrangement
Shift-Net: Image Inpainting via Deep Feature Rearrangement
Zhaoyi Yan
Xiaoming Li
Mu Li
W. Zuo
Shiguang Shan
57
451
0
29 Jan 2018
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
2,119
0
11 Nov 2016
Context Encoders: Feature Learning by Inpainting
Context Encoders: Feature Learning by Inpainting
Deepak Pathak
Philipp Krahenbuhl
Jeff Donahue
Trevor Darrell
Alexei A. Efros
SSL
67
5,297
0
25 Apr 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.8K
77,196
0
18 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
scikit-image: Image processing in Python
scikit-image: Image processing in Python
Stéfan van der Walt
Johannes L. Schonberger
Juan Nunez-Iglesias
François Boulogne
Joshua D. Warner
Neil Yager
Emmanuelle Gouillart
Tony Yu
the scikit-image contributors
SSegGPVLM
190
4,351
0
23 Jul 2014
1