Cheng, Y., Zhao, L., Chen, S., Li, X.: Hyperspectral Unmixing Network Accounting for Spectral Variability Based on a Modified Scaled and a Perturbed Linear Mixing Model. Remote Sens (Basel). 15, 3890 (2023). DOI: 10.3390/rs15153890.
Bazi, Y., Bruzzone, L., Melgani, F.: Automatic Identification of the Number and Values of Decision Thresholds in the Log-Ratio Image for Change Detection in SAR Images. IEEE Geoscience and Remote Sensing Letters. 3, 349–353 (2006). DOI: 10.1109/LGRS.2006.869973.
Inglada, J., Mercier, G.: A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis. IEEE Transactions on Geoscience and Remote Sensing. 45, 1432–1445 (2007). DOI: 10.1109/TGRS.2007.893568.
Du, Y., Zhong, R., Li, Q., Zhang, F.: TransUNet++SAR: Change Detection with Deep Learning about Architectural Ensemble in SAR Images. Remote Sens (Basel). 15, 6 (2022). DOI: 10.3390/rs15010006.
Samadi, F., Akbarizadeh, G., Kaabi, H.: Change detection in SAR images using deep belief net-work: a new training approach based on morphological images. IET Image Process. 13, 2255–2264 (2019). DOI: 10.1049/iet-ipr.2018.6248.
Gong, M., Li, Y., Jiao, L., Jia, M., Su, L.: SAR change detection based on intensity and texture changes. ISPRS Journal of Photogrammetry and Remote Sensing. 93, 123–135 (2014). DOI: 10.1016/j.isprsjprs.2014.04.010.
Wang, P., Zhang, H., Patel, V.M.: SAR Image Despeckling Using a Convolutional Neural Network. IEEE Signal Process Lett. 24, 1763–1767 (2017). DOI: 10.1109/LSP.2017.2758203.
Ramos, L.P., Costa, R.F. da, Medeiros, D. da S. de, Silva, P.B. da, Alves, D.I., Machado, R.: On the Effect of Imperfect Reference Images in SAR Change Detection Based on Bayes' Theorem. In: Anais do XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais. Sociedade Brasileira de Telecomunicações (2022). DOI: 10.14209/sbrt.2022.1570813069.
Pollisetty Pravallika: Ship Tracking and Detection in SAR images using Deep Learning model. International Journal of Creative Research Thoughts. Vol. 10, (2022)
Shafique, A., Cao, G., Khan, Z., Asad, M., Aslam, M.: Deep Learning-Based Change Detection in Remote Sensing Images: A Review. Remote Sens (Basel). 14, 871 (2022). DOI: 10.3390/rs14040871.
Bai, T., Wang, L., Yin, D., Sun, K., Chen, Y., Li, W., Li, D.: Deep learning for change detection in remote sensing: a review. Geo-spatial Information Science. 26, 262–288 (2023). DOI: 10.1080/10095020.2022.208 5633.