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XIONG Wei1,2,GUAN Lai-fu1,WANG Chuan-sheng1,TONG Lei1,LI Li-rong1,LIU Min1
Received:
2019-09-09
Revised:
2019-11-30
Online:
2020-04-25
Published:
2020-04-25
XIONG Wei1,2,GUAN Lai-fu1,WANG Chuan-sheng1,TONG Lei1,LI Li-rong1,LIU Min1.
[1] | Zhang Yong-hong,He Jing,Kan Xi,et al. Summary of road extraction methods for remote sensing images [J].Computer Engineering and Applications,2018,54(13): 1-10.(in Chinese) |
[2] | Wegner J D,Montoya-Zegarra J A,Schindler K.A higher- order CRF model for road network extraction[C]∥Proc of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2013: 1698-1705. |
[3] | Mei Chao,Cao Kai,Wang Jie,et al. A road extraction method based on the aerial image [J].Journal of Shandong University of Technology(Natural Science Edition),2018,32(1): 5-9.(in Chinese) |
[4] | Mnih V,Hinton G E.Learning to detect roads in high-resolution aerial images[C]∥Proc of the 11th European Conference on Computer Vision (ECCV),2010: 210-223. |
[5] | Zhu Zhen-wen, Zhou Li, Liu Jian, et al. Road detection method based on convolutional neural networks[J].Compu- ter Engineering and Design,2017,38(8): 2287-2291.(in Chinese) |
[6] | He Hao,Wang Shi-cheng,Yang Dong-fang,et al. A road extraction method for remote sensing image based on Encoder-Decoder network [J]. |
Acta Geodaetica et Cartographica Sinica,2019,48(3): 330-338.(in Chinese) | |
[7] | Wei Y,Wang Z,Xu M.Road structure refined CNN for road extraction in aerial image[J].IEEE Geoscience and Remote Sensing Letters,2017,14(5): 709-713. |
[8] | Ronneberger O, Fischer P,Brox T.U-Net: Convolutional networks for biomedical image segmentation[C]∥Proc of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),2015: 234-241. |
[9] | He K,Zhang X,Ren S,et al.Deep residual learning for image recognition[C]∥Proc of the 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016: 770-778. |
[10] | Singh P,Dash R.A two-step deep convolution neural network for road extraction from aerial images[C]∥Proc of the 6th International Conference on Signal Processing and Integrated Networks (SPIN) 2019: 660-664. |
[11] | Zhong Z,Li J,Cui W,et al.Fully convolutional networks for building and road extraction:Preliminary results[C]∥Proc of the 36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016: 1591-1594. |
[12] | Panboonyuen T, Jitkajornwanich K,Lawawirojwong S,et al.Road segmentation of remotely-sensed images using deep convolutional neural networks with landscape metrics and conditional random fields[J].Remote Sensing,2017,9(7): 680. |
[13] | Qin X,Zhang Z,Huang C,et al.BASNet: Boundary-aware salient object detection[C]∥Proc of 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2019: 7479-7489. |
[14] | Chen L-C,Papandreou G,Schroff F,et al.Rethinking atrous convolution for semantic image segmentation[J].arXiv: 1706.05587,2017. |
[15] | Boer P-T D,Kroese D P,Mannor S,et al.A tutorial on the cross-entropy method[J].Annals of Operations Research,2005,134(1): 19-67. |
[16] | Wang Z,Simoncelli E P,Bovik A C.Multiscale structural similarity for image quality assessment[C]∥Proc of the 37th Asilomar Conference on Signals,Systems & Computers,2003: 1398-1402. |
[17] | Mattyus G,Luo W,Urtasun R.DeepRoadMapper: Extracting road topology from aerial images[C]∥Proc of the 16th IEEE International Conference on Computer Vision (ICCV),2017: 3458-3466. |
[18] | Mnih V.Machine learning for aerial image labeling [D].Toronto: University of Toronto,2013. |
[19] | Ioffe S,Szegedy C.Batch normalization: Accelerating deep network training by reducing internal covariate shift[C]∥Proc of the 32nd International Conference on Machine Learning (ICML),2015: 448-456. |
[20] | Hahnloser R H R,Seung H S.Permitted and forbidden sets in symmetric threshold-linear networks[C]∥Proc of the 14th Annual Neural Information Processing Systems Conference (NIPS),2001: 217-223. |
[21] | Kingma D P,Ba J L.Adam: A method for stochastic optimization[J].arXiv: 1412.6980,2014. |
[22] | Badrinarayanan V,Kendall A,Cipolla R.SegNet: A deep convolutional encoder-decoder architecture for image segmentation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(12): 2481-2495. |
[23] | Chen L-C,Zhu Y,Papandreou G,et al.Encoder-decoder with atrous separable convolution for semantic image segmentation[J].arXiv: 1802.02611v1,2018. |
附中文参考文献: | |
[1] | 张永宏,何静,阚希,等.遥感图像道路提取方法综述[J].计算机工程与应用,2018,54(13): 1-10. |
[3] | 梅超,曹凯,王杰,等.基于航拍图像的道路提取算法[J].山东理工大学学报(自然科学版),2018,32(1): 5-9. |
[5] | 朱振文,周莉,刘建,等.基于卷积神经网络的道路检测方法[J].计算机工程与设计,2017,38(8): 2287-2291. |
[6] | 贺浩,王仕成,杨东方,等.基于Encoder-Decoder网络的遥感影像道路提取方法[J].测绘学报,2019,48(3): 330-338. |
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