The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Building detection in very high resolution multispectral data with deep learning features
Open accessAbstract
The automated man-made object detection and building extraction from single satellite images is, still, one of the most challenging tasks for various urban planning and monitoring engineering applications. To this end, in this paper we propose an automated building detection framework from very high resolution remote sensing data based on deep convolutional neural networks. The core of the developed method is based on a supervised classification procedure employing a very large training dataset. An MRF model is then responsible for obtaining the optimal labels regarding the detection of scene buildings. The experimental results and the performed quantitative validation indicate the quite promising potentials of the developed approach.
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Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Learning methods for generic object recognition with invariance to pose and lighting
LeCun, Y., Huang, F. J., & Bottou, L. (2004) · Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. · doi:10.1109/cvpr.2004.1315150 · Cited by 1,324
Cited by
DOTA: A Large-Scale Dataset for Object Detection in Aerial Images
Xia, G.-S., Bai, X., Ding, J., Zhu, Z., Belongie, S., Luo, J., Datcu, M., Pelillo, M., & Zhang, L. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00418 · Cited by 3,414
Ball, J. E., Anderson, D. T., & Chan, C. S. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.042609 · Cited by 746
Metadata
- Authors
- Vakalopoulou, M., Karantzalos, K., Komodakis, N., & Paragios, N.
- Venue
- 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
- Publisher
- IEEE
- Published
- 2015-07
- Pages
- 1873-1876
- OpenAlex
- W2028104478
- Cited by
- 298
- References
- 2
- FWCI
- 45.66
- Type
- conference paper
- Language
- en
- Open access
- green
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- Vakalopoulou, M., Karantzalos, K., Komodakis, N., & Paragios, N. (2015). Building detection in very high resolution multispectral data with deep learning features. 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). https://doi.org/10.1109/igarss.2015.7326158
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