Smeulders A W M, Worring M, Santini S, Gupta A, Jain R. Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(12): 1349-1380
[2]
Liu Y, Zhang D S, Lu G J, Ma W Y. A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 2007, 40(1): 262-282
[3]
Zhou Z H, Chen K J, Dai H B. Enhancing relevance feedback in image retrieval using unlabeled data. ACM Transactions on Information Systems, 2006, 24(2): 219-244
[4]
Zhou D Y, Weston J, Gretton A, Bousquet O, Scholkopf B. Ranking on data manifolds. Advances in Neural Information Processing Systems. Cambridge: The MIT Press, 2004. 169-176
[5]
Wang C, Zhao J, He X F, Chen C, Bu J J. Image retrieval using nonlinear manifold embedding. Neurocomputing, 2009, 72(16-18): 3922-3929
[6]
Li Jie, Cheng Yi-Min, Ge Shi-Ming, Zhang Ling. Integrated manifold ranking and region matching for image retrieval. Journal of Chinese Computer Systems, 2008, 29(3): 511-515(李杰, 程义民, 葛仕明, 张玲. 结合流形排序和区域匹配的图像检索. 小型微型计算机系统, 2008, 29(3): 511-515)
[7]
Belkin M, Niyogi P, Sindhwani V. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. The Journal of Machine Learning Research, 2006, 7: 2399-2434
[8]
Huijsmans D P, Sebe N. How to complete performance graphs in content-based image retrieval: add generality and normalize scope. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(2): 245-251
[9]
Liu Qing, Xu Lu-Ping, Ma Yi-De, Wang Yong. Image NMI feature extraction and retrieval method based on pulse coupled neural networks. Acta Automatica Sinica, 2010, 36(7): 931-938(刘勍, 许录平, 马义德, 王勇. 基于脉冲耦合神经网络的图像NMI特征提取及检索方法. 自动化学报, 2010, 36(7): 931-938
[10]
Arevalillo-Herraez M, Ferri F J, Domingo J. A naive relevance feedback model for content-based image retrieval using multiple similarity measures. Pattern Recognition, 43(3): 619-629
[11]
Luo Si-Wei, Zhao Lian-Wei. Manifold learning algorithms based on spectral graph theory. Journal of Computer Research and Development, 2006, 43(7): 1173-1179(罗四维, 赵连伟. 基于谱图理论的流形学习算法. 计算机研究与发展, 2006, 43(7): 1173-1179)
[12]
He J R, Li M J, Zhang H J, Tong H H, Zhang C S. Generalized manifold-ranking-based image retrieval. IEEE Transactions on Image Processing, 2006, 15(10): 3170-3177
[13]
Lin Y Y, Liu T L, Chen H T. Semantic manifold learning for image retrieval. In: Proceedings of the 13th Annual ACM International Conference on Multimedia. New York, USA: ACM, 2005. 249-258
[14]
Wang Zhi-Qiang, Fu Xiang-Hua, Zhao Liang-Hui, Du Wen-Feng. Manifold based semi-supervised learning for content-based image retrieval. Geomatics and Information Science of Wuhan University, 2009, 34(8): 928-931, 935(王志强, 傅向华, 赵良辉, 杜文峰. 基于内容的半监督流体图像检索. 武汉大学学报信息科学版, 2009, 34(8): 928-931, 935)
[15]
Zhang K, Tsang I W, Kwok J T. Improved Nystr？m low-rank approximation and error analysis. In: Proceedings of the 25th International Conference on Machine Learning. New York, USA: ACM, 2008. 1232-1239
