Improved Building Extraction from Remotely Sensed Images by Integration of Encode–Decoder and Edge Enhancement Models
Author:
Funder
Indian Space Research Organisation
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12524-024-01992-1.pdf
Reference45 articles.
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2. Aytekin, O., Ulusoy, I., Erener, A., & Duzgun, H. (2009). Automatic and unsupervised building extraction in complex urban environments from multi spectral satellite imagery. In 2009 4th international conference on recent advances in space technologies, pp 287–291. IEEE. https://doi.org/10.1109/RAST.2009.5158214
3. Bera, S., & Shrivastava, V. K. (2020). Effect of pooling strategy on convolutional neural network for classification of hyperspectral remote sensing images. IET Image Processing, 14(3), 480–486. https://doi.org/10.1049/iet-ipr.2019.0561
4. Bera, S., & Shrivastava, V. K. (2020). Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification. International Journal of Remote Sensing, 41(7), 2664–2683. https://doi.org/10.1080/01431161.2019.1694725
5. Canny, J. (1987). A Computational Approach to Edge Detection, Readings in Computer Vision. In M. A. Fischler & O. Firschien (Eds.), Firschien Morgan Kaufmann Publishers Inc., Los Altos, California
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