[1] [1] PIEDRA-FERNNDEZ J A, ORTEGA G, WANG J Z, et al.. Fuzzy content-based image retrieval for oceanic remote sensing ［J］. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(9): 5422-5431.

[2] [2] ZHU B, RAMSEY M, CHEN H. Creating a large-scale content-based airphoto image digital library ［J］. IEEE Transactions on Image Processing, 2000, 9(1): 163-167.

[3] [3] MAHESHWARY P, SRIVASTAVA N. Prototype system for retrieval of remote sensing images based on color moment and gray level co-occurrence matrix ［J］. International Journal of Computer Science Issues, 2009, 3: 20-23.

[4] [4] LU L ZH, LIU R Y, LIU N. Remote sensing image retrieval using color and texture fused features ［J］. Journal of Image and Graphics, 2004, 9(3): 328-333. (in Chinese)

[5] [5] DEMIR B, BRUZZONE L. A novel active learning method in relevance feedback for content-based remote sensing image retrieval ［J］. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(5): 2323-2334.

[6] [6] GAO H ZH, WAN J W, NIAN Y J, et al.. Fusion classification of hyperspectral image by composite kernels support vector machine ［J］. Opt. Precision Eng., 2011, 19(4): 878-883. (in Chinese)

[7] [7] GUO Y M, LIU Y, OERLEMANS A, et al.. Deep learning for visual understanding: A review ［J］. Neurocomputing, 2016, 187: 27-48.

[8] [8] ALZUBI A, AMIRA A, RAMZAN N. Semantic content-based image retrieval: A comprehensive study ［J］. Journal of Visual Communication and Image Representation, 2015, 32: 20-54.

[9] [9] LUUS F P S, SALMON B P, VAN DEN BERGH F, et al.. Multiview deep learning for land-use classification ［J］. IEEE Geoscience and Remote Sensing Letters, 2015, 12(12): 2448-2452.

[10] [10] XIONG CH ZH, SHAN Y M, GUO F H. Image retrieval method based on image principal part detection ［J］. Opt. Precision Eng., 2017, 25(3): 792-798. (in Chinese)

[11] [11] LIU H L, LI B A, LYU X Q, et al.. Image retrieval based on deep convolutional neural network［J/OL］. Application Research of Computers, 2017, 34(12), ［2017-01-23］. http: //www.arocmag.com/article/02-2017-12-007.html. (in Chinese)

[12] [12] HUBEL D H, WIESEL T N. Receptive fields, binocular interaction and functional architecture in the cats visual cortex ［J］. The Journal of Physiology, 1962, 160(1): 106-154.

[13] [13] FUKUSHIMA K, MIYAKE S, ITO T. Neocognitron: A neural network model for a mechanism of visual pattern recognition ［J］. IEEE Transactions on Systems, Man, and Cybernetics, 1983, SMC-13(5): 826-834.

[14] [14] LECUN Y, BOTTOU L, BENGIO Y, et al.. Gradient-based learning applied to document recognition ［J］. Proceedings of the IEEE, 1998, 86(11): 2278-2324.

[15] [15] LUO J X, LIN CH H, WANG J P, et al.. Accurate image locating combining deep convolution network with SURF registering ［J］. Opt. Precision Eng., 2017, 25(2): 469-476. (in Chinese)

[16] [16] HINTON G E, SRIVASTAVA N, KRIZHEVSKY A, et al.. Improving neural networks by preventing co-adaptation of feature detectors ［J］. Computer Science, 2012, 3(4): 212-223.

[17] [17] ZHANG H Q, LIU X Y, YANG S, et al.. Retrieval of remote sensing images based on semisupervised deep learning ［J］. Journal of Remote Sensing, 2017, 21(3): 406-414. (in Chinese)