K-means Pelican Optimization Algorithm based Search Space Reduction for Remote Sensing Image Retrieval
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12524-024-01994-z.pdf
Reference32 articles.
1. Cao, R., Zhang, Q., Zhu, J., Li, Q., Li, Q., Liu, B., & Qiu, G. (2020). Enhancing remote sensing image retrieval using a triplet deep metric learning network. International Journal of Remote Sensing, 41(2), 740–751. https://doi.org/10.1080/2150704X.2019.1647368
2. Chavda, S., & Goyani, M. (2020). Hybrid approach to content-based image retrieval using modified multi-scale LBP and color features. SN Computer Science, 1(6), 305. https://doi.org/10.1007/s42979-020-00321-w
3. Cheng, Q., Gan, D., Fu, P., Huang, H., & Zhou, Y. (2021). A novel ensemble architecture of residual attention-based deep metric learning for remote sensing image retrieval. Remote Sensing, 13(17), 3445. https://doi.org/10.3390/rs13173445
4. Dai, D., & Yang, W. (2011). Satellite image classification via two-layer sparse coding with biased image representation. IEEE Geoscience and Remote Sensing Letters, 8(1), 173–176. https://doi.org/10.1109/LGRS.2010.2055033
5. Ding, C., Wang, M., Zhou, Z., Huang, T., Wang, X., & Li, J. (2023). Siamese transformer network-based similarity metric learning for cross-source remote sensing image retrieval. Neural Computing and Applications, 35(11), 8125–8142. https://doi.org/10.1007/s00521-022-08092-6
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