Wei XIONG, Laifu GUAN, Lei TONG, Chuansheng WANG, Min LIU, Chunyan ZENG. Research on Road Extraction Algorithm Based on Residual Neural Networks[J]. Optoelectronic Technology, 2020, 40(1): 6.
[2]EslamiM, FaezK. Automatic traffic monitoring using satellite images [C]. Proceedings of the 2nd International Conference on Computer Engineering and Technology(ICCET),Chengdu,China, 2010:V6130-V6135.
[3]ZhengS, LiuJ, ShiW, et al. Road central contour extraction from high resolution satellite image using tensor voting framework [C]. Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, ,China, 2006:3248-3253.
[4]ZhuD, WenX, LingC. Road extraction based on the algorithms of MRF and hybrid model of SVM and FCM [C]. Proceedings of the 2011 International Symposium on Image and Data Fusion(ISIDF), ,,China, 2011: 1-4.
[5]WegnerJ D, Montoya ZegarraJ A, SchindlerK. A higher-order CRF model for road network extraction [C]. Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition(CVPR), ,,USA, 2013: 1698-1705.
[6] Wegner J D, WegnerJ D, WegnerJ D, Montoya ZegarraJ A, Montoya ZegarraJ A, Montoya Zegarra J A, Schindler K, SchindlerK, SchindlerK. Road networks as collections of minimum cost paths[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 108(2): 128-137.
[7] DasS, DasS, Das S, Mirnalinee T T, MirnalineeT T, MirnalineeT T, Varghese K, VargheseK, VargheseK. Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3906-3931.
[9]ZhangZ, WangY, LiuQ, et al. A CNN based functional zone classification method for aerial images [C]. Proceedings of the 36th IEEE International Geoscience and Remote Sensing Symposium(IGARSS), Beijing,China, 2016: 5449-5452.
[10] MaggioriE, MaggioriE, MaggioriE, Maggiori E, Tarabalka Y, TarabalkaY, TarabalkaY, TarabalkaY, CharpiatG, CharpiatG, CharpiatG, Charpiat G. Convolutional neural networks for large-scale remote-sensing image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(2): 645-657.
[11]MnihV, HintonG E. Learning to detect roads in high-resolution aerial images [C]. Proceedings of the 11th European Conference on Computer Vision(ECCV), , , 2010:210-223.
[12] WeiY, WeiY, Wei Y, Wang Z, WangZ, WangZ, XuM, XuM, Xu M. Road structure refined CNN for road extraction in aerial image[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(5): 709-713.
[13]RonnebergerO, FischerP, BroxT. U-Net: Convolutional networks for biomedical image segmentation [C]. Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI), , , 2015: 234-241.
[14]HeK, ZhangX, RenS, et al. Deep residual learning for image recognition [C]. Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Las Vegas, USA, 2016: 770-778.
[15]SinghP, DashR. A two-step deep convolution neural network for road extraction from aerial images [C]. Proceedings of the 6th International Conference on Signal Processing and Integrated Networks (SPIN), ,, 2019: 660-664.
[16] HongZ, HongZ, HongZ, Hong Z, Ming D, MingD, MingD, MingD, ZhouK, ZhouK, ZhouK, Zhou K. Road extraction from a high spatial resolution remote sensing image based on richer convolutional features[J]. IEEE Access, 2018, 6(1): 46988-47000.
[17]ZhongZ, LiJ, CuiW, et al. Fully convolutional networks for building and road extraction: preliminary results [C]. Proceedings of the 36th IEEE International Geoscience and Remote Sensing Symposium(IGARSS), Beijing,China, 2016:1591-1594.
[20]QinX B, ZhangZ C, HuangC Y, et al. BASNet: Boundary-aware salient object detection [C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), , USA, 2019:7479-7489.
[21] Devalla S K, DevallaS K, DevallaS K, DevallaS K, Renukanand P K, RenukanandP K, RenukanandP K, RenukanandP K, Sreedhar B K, SreedharB K, SreedharB K, SreedharB K. DRUNET: A dilated-residual u-net deep learning network to digitally stain optic nerve head tissues in optical coherence tomography images[J]. Biomedical Optics Express, 2018, 9(7): 3244-3265.
[22]MnihV. Machine learning for aerial image labeling [D]. Canada: University of Toronto, 2013.
[25] BadrinarayananV, BadrinarayananV, Badrinarayanan V, Kendall A, KendallA, KendallA, CipollaR, CipollaR, 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.
[26]ChaurasiaA, CulurcielloE. LinkNet: Exploiting encoder representations for efficient semantic segmentation [C]. Proceedings of the IEEE Visual Communications and Image Processing(VCIP), , , , 2017:1-4.
熊炜, 管来福, 童磊, 王传胜, 刘敏, 曾春艳. 基于残差神经网络的道路提取算法研究[J]. 光电子技术, 2020, 40(1): 6. Wei XIONG, Laifu GUAN, Lei TONG, Chuansheng WANG, Min LIU, Chunyan ZENG. Research on Road Extraction Algorithm Based on Residual Neural Networks[J]. Optoelectronic Technology, 2020, 40(1): 6.