Possibilities of deep learning neural networks for satellite image recognition

The main problem solved in this project is the analysis of big data using a system of computer processing and recognition of satellite images, based on a deep neural network architecture. The goal of the project is to develop methodological, theoretical and practical aspects of building such systems...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1703; no. 1; pp. 12031 - 12036
Main Authors Averkin, A N, Yarushev, S A
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.12.2020
Subjects
Artificial neural networks
Computer architecture
Deep learning
Economic impact
Fresh water
Impact analysis
Natural disasters
Neural networks
Object recognition
Physics
Prediction models
Satellite imagery
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Summary:The main problem solved in this project is the analysis of big data using a system of computer processing and recognition of satellite images, based on a deep neural network architecture. The goal of the project is to develop methodological, theoretical and practical aspects of building such systems in poorly formalized subject areas, as well as to study the possibilities and advantages of building predictive models for analyzing fresh water reserves and predicting the direction, speed and nature of the spread of large fires using such systems. and assessments of the economic impact of these natural disasters.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1703/1/012031