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Review on Deep Learning in Remote Sensing Image Classification
, Preeti Rajkumar Komati
Published in Science & Engineering Research Support soCiety
Volume: 13.0
Issue: special issue
Pages: 1223.0 - 1227.0
Remote sensing image scene classification has a wide scope of applications and hence has been receiving remarkable attention. Nowadays, Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing image analysis over the past few years. This paper first provides a comprehensive review of the recent progress in remote sensing applications. The existing remote-sensing classification methods are categorized into four main categories according to the features they use: manually feature-based methods, unsupervised feature learning methods, supervised feature learning methods, and object based methods[15]. This article then focuses on evaluating the available and public remote-sensing datasets. Finally, a conclusion regarding the current state of art methods and directions for future research are presented.
About the journal
JournalInternational Journal of Future Generation Communication and Networking
PublisherScience & Engineering Research Support soCiety
Open Access0