Overview Of Satellite Image Recognition Models
Alexey Averkin, Sergey Yarushev

TL;DR
This paper reviews existing satellite image recognition models, compares deep learning methods, and discusses future applications like fire detection and macro-economic forecasting using satellite data.
Contribution
It provides a comprehensive analysis of current satellite image recognition models and explores their potential for future applications in fire detection and economic forecasting.
Findings
Deep learning methods are effective for satellite image recognition.
Existing models have limitations that need addressing for specific applications.
The analysis lays groundwork for developing specialized recognition and forecasting models.
Abstract
In this article, the analysis of existing models of satellite image recognition was carried out, the problems in the field of satellite image recognition as a source of information were considered and analyzed, deep learning methods were compared, and existing image recognition methods were analyzed. The results obtained will be used as a basis for the prospective development of a fire recognition model based on satellite images and the use of recognition results as input data for a cognitive model of forecasting the macro-economic situation based on fuzzy cognitive maps.
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Taxonomy
TopicsTechnology and Human Factors in Education and Health · Advanced Data Processing Techniques · Environmental Sustainability and Technology
