Metric-Learning based Deep Hashing Network for Content Based Retrieval of Remote Sensing Images
| Autor: | Nicu Sebe, Subhankar Roy, Enver Sangineto, Begum Demir |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Computer science Computer Vision and Pattern Recognition (cs.CV) Feature extraction Hash function Computer Science - Computer Vision and Pattern Recognition 0211 other engineering and technologies 02 engineering and technology Overfitting Geotechnical Engineering and Engineering Geology Metric space Metric (mathematics) Binary code Electrical and Electronic Engineering 021101 geological & geomatics engineering Remote sensing |
| Zdroj: | IEEE Geoscience and Remote Sensing Letters |
| DOI: | 10.48550/arxiv.1904.01258 |
| Popis: | Hashing methods have been recently found very effective in retrieval of remote sensing (RS) images due to their computational efficiency and fast search speed. The traditional hashing methods in RS usually exploit hand-crafted features to learn hash functions to obtain binary codes, which can be insufficient to optimally represent the information content of RS images. To overcome this problem, in this paper we introduce a metric-learning based hashing network, which learns: 1) a semantic-based metric space for effective feature representation; and 2) compact binary hash codes for fast archive search. Our network considers an interplay of multiple loss functions that allows to jointly learn a metric based semantic space facilitating similar images to be clustered together in that target space and at the same time producing compact final activations that lose negligible information when binarized. Experiments carried out on two benchmark RS archives point out that the proposed network significantly improves the retrieval performance under the same retrieval time when compared to the state-of-the-art hashing methods in RS. Comment: Accepted to IEEE Geoscience and Remote Sensing Letters. For code visit: https://github.com/MLEnthusiast/MHCLN |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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