High-efficiency scene classification based on deep compressed-domain feature

Remote sensing image (RSI) scene classification has become a more and more fundamental issue in satellite and UAV time-sensitive applications. However, as the volume and velocity of RSIs are undergoing an explosive growth, traditional effective technologies claim a huge amount of computing resources...

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Bibliographic Details
Main Authors:	Cheng Li, Baojun Zhao, Boya Zhao, Wenzheng Wang, Chenhui Duan
Format:	Article
Language:	English
Published:	Wiley 2019-08-01
Series:	The Journal of Engineering
Subjects:	remote sensing image coding data compression geophysical image processing image classification feature extraction image representation convolutional neural nets computing resources in-orbit processing capacity deep feature representation framework body information raw JPEG2000 codestream compressed-domain convolutional neural network high-level representation effective classification high classification accuracy high-efficiency scene classification compressed-domain feature remote sensing image scene classification RSI satellite application header information UAV time-sensitive application
Online Access:	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0266

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https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0266

High-efficiency scene classification based on deep compressed-domain feature

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