Targeted change detection in remote sensing images

Autor: Vladimir Ignatiev, Viktor Lobachev, Evgeny Burnaev, Alexey Trekin, Georgy Potapov
Rok vydání: 2018
Předmět:
FOS: Computer and information sciences
Computer science
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
Image processing
02 engineering and technology
Computational Engineering
Finance
and Science (cs.CE)

03 medical and health sciences
0302 clinical medicine
0202 electrical engineering
electronic engineering
information engineering

FOS: Electrical engineering
electronic engineering
information engineering

Satellite imagery
Computer Science - Computational Engineering
Finance
and Science

Remote sensing
business.industry
Deep learning
Image and Video Processing (eess.IV)
Problem statement
Electrical Engineering and Systems Science - Image and Video Processing
Object (computer science)
Remote sensing (archaeology)
030221 ophthalmology & optometry
020201 artificial intelligence & image processing
Satellite
Artificial intelligence
business
Change detection
Zdroj: ICMV
DOI: 10.48550/arxiv.1803.05482
Popis: Recent developments in the remote sensing systems and image processing made it possible to propose a new method of the object classification and detection of the specific changes in the series of satellite Earth images (so called targeted change detection). In this paper we propose a formal problem statement that allows to use effectively the deep learning approach to analyze time-dependent series of remote sensing images. We also introduce a new framework for the development of deep learning models for targeted change detection and demonstrate some cases of business applications it can be used for.
Comment: 10 pages, 1 figures, 1 table
Databáze: OpenAIRE