Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks

4 July 2020

Papers citing "Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks"

8 / 8 papers shown

Title
Bayesian Despeckling of Structured Sources Ali Zafari Shirin Jalali 55 0 0 21 Jan 2025
Hiding Local Manipulations on SAR Images: a Counter-Forensic Attack S. Mandelli E. D. Cannas Paolo Bestagini Stefano Tebaldini Stefano Tubaro 37 1 0 09 Jul 2024
Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise Removal Xiao Siyao Huang Libing Zhang Shunsheng 52 0 0 06 Jul 2024
Self-supervised remote sensing feature learning: Learning Paradigms, Challenges, and Future Works Chao Tao Ji Qi Mingning Guo Qing Zhu Haifeng Li SSL 37 57 0 15 Nov 2022
As if by magic: self-supervised training of deep despeckling networks with MERLIN Emanuele Dalsasso L. Denis F. Tupin 18 64 0 25 Oct 2021
The potential of self-supervised networks for random noise suppression in seismic data C. Birnie M. Ravasi T. Alkhalifah Sixiu Liu 34 55 0 15 Sep 2021
A speckle filter for Sentinel-1 SAR Ground Range Detected data based on Residual Convolutional Neural Networks A. Sebastianelli M. P. D. Rosso Silvia Liberata Ullo Paolo Gamba 30 14 0 19 Apr 2021
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning Emanuele Dalsasso Inès Meraoumia L. Denis F. Tupin 29 4 0 01 Feb 2021