[1] Que H Y, Huang H X, Xu J M. Road edge detection based on dual-threshold SSDA template matching[J]. Remote Sensing for Land & Resources, 26, 29-33(2014).
[2] Xu Q Y, Li Y, Lin W J et al. Remote sensing image segmentation based on information clustering[J]. Journal of China University of Mining & Technology, 46, 209-214(2017).
[3] Li J F, Wen Z Q, Hu Y X et al. Road extraction from remote sensing images based on improved regional growth[J]. Computer Engineering and Applications, 52, 209-213, 238(2016).
[4] Lang W H, Shen Y, Ang A et al. Segmentation of SAR sea ice image based on region splitting and adaptive refinement process[J]. Journal of Remote Sensing, 19, 864-872(2015).
[5] Guo J, Jiang J, Cao S X. Automatic building segmentation from remote sensing images using multi-layer level set framework[J]. Infrared and Laser Engineering, 43, 1332-1337(2014).
[6] Shi G M, Suo J D, Huang C et al. Remote sensing image edge-detection based on improved Canny operator[J]. Journal of Dalian Jiaotong University, 36, 87-90, 108(2015).
[7] Tan Y, Huang H X, Xu J M et al. Road edge detection from remote sensing image based on improved Sobel operator[J]. Remote Sensing for Land & Resources, 28, 7-11(2016).
[8] Dai J D, Liu Y D, Mao X Y et al. Registration based on NSCT-domain FAST corner detection for infrared and visible images of electrical equipment[J]. Electrical Measurement & Instrumentation, 56, 108-114(2019).
[10] Wang B, Gao X B, Li J et al. A level set method with shape priors by using locality preserving projections[J]. Neurocomputing, 170, 188-200(2015).
[11] Amberg B, Vetter T. Optimal landmark detection using shape models and branch and bound. [C]∥2011 International Conference on Computer Vision, November 6-13, 2011, Barcelona, Spain. New York: IEEE, 455-462(2011).
[14] Zhou M F, Wang X L, Wang L et al. Convolutional neural network models for high spatial resolution satellite imagery classification[J]. Journal of Image and Graphics, 22, 996-1007(2017).
[15] Gerke M. Use of the stair vision library within the ISPRS 2D semantic labeling benchmark (Vaihingen)[R]. Netherlands: University of Twente(2014).
[16] Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets[J]. Neural Computation, 18, 1527-1554(2006).
[17] Salakhutdinov R, Hinton G E. Deep Boltzmann machines[C]∥Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, April 16-18, 2009, Clearwater Beach, Florida, USA., 448-455(2009).
[18] Norouzi M, Ranjbar M, Mori G. Stacks of convolutional Restricted Boltzmann Machines for shift-invariant feature learning. [C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL, USA. New York: IEEE, 2735-2742(2009).
[19] Salakhutdinov R. Learning deep generative models[J]. Annual Review of Statistics and Its Application, 2, 361-385(2015).
[20] Hinton G E. Training products of experts by minimizing contrastive divergence[J]. Neural Computation, 14, 1771-1800(2002).
[21] Gibbs sampling[J/OL]. -01-01) https:∥www.researchgate.net/publication/259088117_Markov_Chain_Monte_Carlo_and_Gibbs_[2019-07-28]. Sampling.(2004).
[22] Li C M, Xu C Y, Gui C F et al. Distance regularized level set evolution and its application to image segmentation[J]. IEEE Transactions on Image Processing, 19, 3243-3254(2010).
[23] Chan T F, Sandberg B Y, Vese L A. Active contours without edges for vector-valued images[J]. Journal of Visual Communication and Image Representation, 11, 130-141(2000).
[24] Li X, Zhao F, Guo Y. Conditional restricted Boltzmann machines for multi-label learning with incomplete labels[C]∥Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS)2015, M, 635-643(2015).
[25] Zhang J, Wang X L, Yang J G. Shape modeling method based on deep learning[J]. Chinese Journal of Computers, 41, 132-144(2018).
