Training Convolutional Neural Networks with Multi-Size Images and Triplet Loss for Remote Sensing Scene Classification

Training Convolutional Neural Networks with Multi-Size Images and Triplet Loss for Remote Sensing Scene Classification

Many remote sensing scene classification algorithms improve their classification accuracy by additional modules, which increases the parameters and computing overhead of the model at the inference stage. In this paper, we explore how to improve the classification accuracy of the model without adding...

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Bibliographic Details
Main Authors: Jianming Zhang, Chaoquan Lu, Jin Wang, Xiao-Guang Yue, Se-Jung Lim, Zafer Al-Makhadmeh, Amr Tolba
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sensors
Subjects:
dropout
triplet loss
training with multi-size images
remote sensing scene classification
Online Access:https://www.mdpi.com/1424-8220/20/4/1188

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https://www.mdpi.com/1424-8220/20/4/1188

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