Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to transfer successful pre-trained deep CNNs to...

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Bibliographic Details
Main Authors: Jie Wang, Chang Luo, Hanqiao Huang, Huizhen Zhao, Shiqiang Wang
Format: Article
Language:English
Published: MDPI AG 2017-03-01
Series:Remote Sensing
Subjects:
convolutional neural network
remote scene classification
general feature
principle component analysis
deep learning
Online Access:http://www.mdpi.com/2072-4292/9/3/225

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http://www.mdpi.com/2072-4292/9/3/225

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