Application of Pattern Recognition to Remote Sensing *

2019 ◽  
pp. 65-106
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition

scholarly journals Pattern Recognition in Remote Sensing

2010 ◽  
Vol 31 (10) ◽  
pp. 1069-1070 ◽  
Author(s):  
Selim Aksoy ◽  
Nicolas H. Younan ◽  
Lorenzo Bruzzone
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition

scholarly journals Mapping the Unseen: Exploiting Super-Resolution for Semantic Segmentation in Low-Resolution Images

2020 ◽  
Author(s):  
Matheus B. Pereira ◽  
Jefersson Alex Dos Santos
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition ◽  
Super Resolution ◽  
Remote Sensing Data ◽  
Semantic Segmentation ◽  
The Other ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Remote Sensing Images ◽  
Low Resolution

High-resolution aerial images are usually not accessible or affordable. On the other hand, low-resolution remote sensing data is easily found in public open repositories. The problem is that the low-resolution representation can compromise pattern recognition algorithms, especially semantic segmentation. In this M.Sc. dissertation1 , we design two frameworks in order to evaluate the effectiveness of super-resolution in the semantic segmentation of low-resolution remote sensing images. We carried out an extensive set of experiments on different remote sensing datasets. The results show that super-resolution is effective to improve semantic segmentation performance on low-resolution aerial imagery, outperforming unsupervised interpolation and achieving semantic segmentation results comparable to highresolution data.

Spectral pattern recognition in IR remote sensing

1983 ◽  
Vol 22 (17) ◽  
pp. 2699 ◽  
Author(s):  
Alexander S. Zachor
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition ◽  
Spectral Pattern
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