1 |
Badrinarayanan, V., A. Kendall, and R. Cipolla, 2017. SegNet: A deep convolutional encoder-decoder architecture for image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12): 2481-2495.
DOI
|
2 |
Fang, B., L. Pan, and R. Kou, 2019. Dual learningbased siamese framework for change detection using bi-temporal VHR optical remote sensing image, Remote Sensing, 11(11): 1292.
DOI
|
3 |
Hou, B., Q. Liu, H. Wang, and Y. Wang, 2020. From W-Net to CDGAN: Bitemporal change detection vis deep learning techniques, IEEE Transactions on Geoscience and Remote Sensing, 58(3): 1790-1802.
DOI
|
4 |
Lee, S., H. Yoo, and M. Kim, 2011. Requirements analysis on the acquisition and sharing of land-monitoring data, Seoul Studies, 12(3): 185-201.
|
5 |
Zhan, Y., K. Fu, M. Yan, X. Sun, H .Wang, and X. Qiu, 2017. Change detection based on deep siamese convolutional network for optical aerial images, IEEE Geoscience and Remote Sensing Letters, 14(10): 1845-1849.
DOI
|
6 |
Li, L., C. Wang, H. Zhang, B. Zhang, and F. Wu, 2019. Urban building change detection in SAR images using combined differential image and residual U-Net network, Remote Sensing, 11(9): 1091.
DOI
|
7 |
Liu, J., K. Chen, G. Xu, X. Sun, M. Yan, W. Diao, and H. Han, 2020. Convolutional neural network-based transfer learning for optical aerial images change detection, IEEE Geoscience and Remote Sensing Letters, 17(1): 127-131.
DOI
|
8 |
Lu, D., P. Mausel, E. Brondizio, and E. Moran, 2004. Change detection techniques, International Journal of Remote Sensing, 25(12): 2365-2401.
DOI
|
9 |
Lu, D., G. Li, and E. Moran, 2014. Current situation and needs of change detection techniques, International Journal of Image and Data Fusion, 5(1): 13-38.
DOI
|
10 |
Peng, D., Y. Zhang, and H. Guan, 2019. End-to-end change detection for high resolution satellite images using improved UNet++, Remote Sensing, 11(11): 1382.
DOI
|
11 |
Zhang, W. and X. Lu, 2019. The spectral-spatial joint learning for change detection in multispectral imagery, Remote Sensing, 11(3): 240.
DOI
|
12 |
Zhou, Z., M.M.R. Siddiquee, N. Tajbakhsh, and J. Liang, 2018. Unet++: A nested u-net architecture for medical image segmentation. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer, Cham, pp. 3-11.
|