Building segmentation through a gated graph convolutional neural network with deep structured feature embedding

Author:

Shi Yilei,Li Qingyu,Zhu Xiao XiangORCID

Funder

European Research Council

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference31 articles.

1. Akilan, T., Wu, Q.M., Jiang, W., 2017. A feature embedding strategy for high-level CNN representations from multiple convnets. In Proc. IEEE Conf. Signal and Information Processing, pp. 1195–1199.

2. Badrinarayanan, V., Handa, A., Cipolla, R., 2015. Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling, arXiv preprint arXiv:1505.07293.

3. Building footprint extraction from VHR remote sensing images combined with normalized DSMs using fused fully convolutional networks;Bittner;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2018

4. Bruna, J., Zaremba, W., Szlam, A., LeCun, Y., 2013. Spectral networks and locally connected networks on graphs, arXiv preprint arXiv:1312.6203.

5. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs;Chen;IEEE Trans. Pattern Anal. Mach. Intell.,2017

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