https://orcid.org/0000-0002-1457-5388
References
- Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti. 2002. “A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms.” Geoscience and Remote Sensing, IEEE Transactions On 40 (11): 2375–2383. doi:10.1109/TGRS.2002.803792.
- Crosetto, M., O. Monserrat, M. Cuevas-González, N. Devanthéry, and B. Crippa. 2016. “Persistent Scatterer Interferometry: A Review.” ISPRS Journal of Photogrammetry and Remote Sensing 115: 78–89. doi:10.1016/j.isprsjprs.2015.10.011.
- Deng, Z., K. Yinghai, H. Gong, L. Xiaojuan, and L. Zhenhong. 2017. “Land Subsidence Prediction in Beijing Based on PS-InSAR Technique and Improved Grey-Markov Model.” GIScience & Remote Sensing 54 (6): 797–818. doi:10.1080/15481603.2017.1331511.
- Ferretti, A., A. Fumagalli, F. Novali, C. Prati, F. Rocca, and A. Rucci. 2011. “A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR.” IEEE Transactions on Geoscience and Remote Sensing 49 (9): 3460–3470. doi:10.1109/TGRS.2011.2124465.
- Ferretti, A., C. Prati, and F. Rocca. 2001. “Permanent Scatterers in SAR Interferometry.” Geoscience and Remote Sensing, IEEE Transactions On 39 (1): 8–20. doi:10.1109/36.898661.
- Gehring, J., M. Auli, D. Grangier, D. Yarats, and Y. N. Dauphin. 2017. “Convolutional Sequence to Sequence Learning.” arXiv Preprint arXiv 1705: 03122.
- Huang, G., Z. Liu, L. Van Der Maaten, and K. Q. Weinberger. 2017. “Densely Connected Convolutional Networks.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Hawaii.
- Kim, S.-W., T. H. Shimon Wdowinski, F. A. Dixon, J. W. Kim, and J.-S. Won. 2010. “Measurements and Predictions of Subsidence Induced by Soil Consolidation Using Persistent Scatterer InSAR and a Hyperbolic Model.” Geophysical Research Letters 37 (5). doi:10.1029/2009GL041644.
- Ma, P., and H. Lin. 2016. “Robust Detection of Single and Double Persistent Scatterers in Urban Built Environments.” IEEE Transactions on Geoscience and Remote Sensing 54 (4): 2124–2139. doi:10.1109/TGRS.2015.2496193.
- Ronneberger, O., P. Fischer, and T. Brox. 2015. “U-net: Convolutional Networks for Biomedical Image Segmentation.” Paper presented at the International Conference on Medical image computing and computer-assisted intervention, Munich, Germany.
- Zhu, X. X., D. Tuia, L. Mou, G.-S. Xia, L. Zhang, X. Feng, and F. Fraundorfer. 2017. “Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources.” IEEE Geoscience and Remote Sensing Magazine 5 (4): 8–36. doi:10.1109/MGRS.2017.2762307.