Object-oriented remote sensing image information extraction method based on multi-classifier combination and deep learning algorithm

2021 ◽  
Vol 141 ◽  
pp. 32-36
Author(s):  
Qulin Tan ◽  
Bin Guo ◽  
Jun Hu ◽  
Xiaofeng Dong ◽  
Jiping Hu
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Information Extraction ◽  
Extraction Method ◽  
Learning Algorithm ◽  
Object Oriented ◽  
Remote Sensing Image ◽  
Classifier Combination ◽  
Image Information ◽  
Deep Learning Algorithm

scholarly journals Remote Sensing Image Building Extraction Method Based on Deep Learning

2020 ◽  
Vol 1631 ◽  
pp. 012010
Author(s):  
Minshui Wang ◽  
Mingchang Wang ◽  
Guodong Yang ◽  
Ziwei Liu
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Extraction Method ◽  
Remote Sensing Image ◽  
Building Extraction ◽  
Image Building

Gurbantunggut Desert Haloxylon Forest NDVI Time Effect - Based on Phenological Changes and the Image of MODIS

2012 ◽  
Vol 433-440 ◽  
pp. 5409-5414
Author(s):  
Tie Cheng Huang ◽  
Shu Jiang Chen ◽  
Min Hou ◽  
Ge Li Shi ◽  
Zhen Xia Shi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information Extraction ◽  
Remote Sensing Image ◽  
Time Effect ◽  
Gurbantunggut Desert ◽  
Information Analysis ◽  
Time Effects ◽  
Image Information ◽  
Phenological Changes ◽  
Gurbantünggüt Desert

Remote sensing image information extraction research is one of the key problems of remote sensing research, it is also one of the hot and difficult points in remote sensing research., In this paper,NDVI images for the study of synthesis of haloxylon ammdendron forest 16 days of MODIS is taken as research object, aimed at improving the precision of information extraction, focuses on the NDVI time effects on phenology of haloxylon ammdendron woodland response, tell woodland diagnosis point of information, using diagnostic points of haloxylon forest information analysis and extraction of results and field visits, mutatis mutandis, the results showed information extraction accuracy has improved.

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