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An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation

An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation

M. B. Pereira
J. A. dos Santos
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Papers citing "An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation"

2 / 2 papers shown
Title
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
201
5,176
0
16 Sep 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
446
15,645
0
02 Nov 2015