ResUNet-a: a deep learning framework for semantic segmentation of
remotely sensed data

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ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

1 April 2019

F. Diakogiannis

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Papers citing "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data"

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Title
Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images Rui Li Shunyi Zheng Chenxi Duan Ce Zhang Jianlin Su P. M. Atkinson SSeg 179 423 0 03 Sep 2020
MSDU-net: A Multi-Scale Dilated U-net for Blur Detection Fan Yang X. Xiao 97 15 0 05 Jun 2020
Learning Global and Local Features of Normal Brain Anatomy for Unsupervised Abnormality Detection Kazuma Kobayashi Ryuichiro Hataya Y. Kurose Amina Bolatkan M. Miyake Hirokazu Watanabe Masamichi Takahashi J. Itami Tatsuya Harada Ryuji Hamamoto MedIm 63 1 0 26 May 2020
A global method to identify trees outside of closed-canopy forests with medium-resolution satellite imagery J. Brandt F. Stolle 63 3 0 13 May 2020
Res-CR-Net, a residual network with a novel architecture optimized for the semantic segmentation of microscopy images H. Abdallah Asiri G. Liyanaarachchi Maranda Saigh Samantha Silvers S. Arslanturk D. Taatjes L. Larsson B. Jena D. Gatti SSeg 57 9 0 14 Apr 2020
ResUNet++: An Advanced Architecture for Medical Image Segmentation Debesh Jha P. Smedsrud Michael A. Riegler Dag Johansen Thomas de Lange Pål Halvorsen H. Johansen SSeg 141 992 0 16 Nov 2019
Deep learning on edge: extracting field boundaries from satellite images with a convolutional neural network F. Waldner F. Diakogiannis 153 216 0 26 Oct 2019