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Open AccessArticle

Coarse-to-Fine Deep Metric Learning for Remote Sensing Image Retrieval

by Min-Sub Yun 1,†, Woo-Jeoung Nam 2,† and Seong-Whan Lee 1,2,3,*
1
Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
2
Department of Computer and Radio Communication Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
3
Department of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2020, 12(2), 219; https://doi.org/10.3390/rs12020219
Received: 6 December 2019 / Revised: 3 January 2020 / Accepted: 7 January 2020 / Published: 8 January 2020
Remote sensing image retrieval (RSIR) is the process of searching for identical areas by investigating the similarities between a query image and the database images. RSIR is a challenging task owing to the time difference, viewpoint, and coverage area depending on the shooting circumstance, resulting in variations in the image contents. In this paper, we propose a novel method based on a coarse-to-fine strategy, which makes a deep network more robust to the variations in remote sensing images. Moreover, we propose a new triangular loss function to consider the whole relation within the tuple. This loss function improves the retrieval performance and demonstrates better performance in terms of learning the detailed information in complex remote sensing images. To verify our methods, we experimented with the Google Earth South Korea dataset, which contains 40,000 images, using the evaluation metric [email protected] In all experiments, we obtained better performance results than those of the existing retrieval training methods. Our source code and Google Earth South Korea dataset are available online. View Full-Text
Keywords: remote sensing image retrieval (RSIR); deep metric learning; convolutional neural networks; contents based image retrieval (CBIR); deep learning remote sensing image retrieval (RSIR); deep metric learning; convolutional neural networks; contents based image retrieval (CBIR); deep learning
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MDPI and ACS Style

Yun, M.-S.; Nam, W.-J.; Lee, S.-W. Coarse-to-Fine Deep Metric Learning for Remote Sensing Image Retrieval. Remote Sens. 2020, 12, 219.

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