Targeted Change Detection in Remote Sensing Images

被引：5

作者：

Ignatiev, V. ^{[1
]}

Trekin, A. ^{[1
]}

Lobachev, V. ^{[1
]}

Potapov, G. ^{[1
]}

Burnaev, E. ^{[1
]}

机构：

[1] Skolkovo Inst Sci & Technol, Moscow, Russia

来源：

ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2018) | 2019年 / 11041卷

关键词：

remote sensing; change detection; satellite imagery; computer vision; deep learning;

D O I：

10.1117/12.2523141

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 develop 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.

引用

页数：6

共 34 条

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[Anonymous], 2018, OP DAT PROGR

[2]

[Anonymous], 2015, P SPIE

[3]

[Anonymous], LNCS

[4]

Burnaev E, P SPIE

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