[1] R. Datta, D. Joshi, J. Li and J. Z. Wang, “Image retrieval: ideas, influences and trends of the new age,” ACM Computing Surveys, vol. 40, no. 2, 2008.
[2] مریم تقیزاده و عبداله چالهچاله، »مدلی بهمنظور بازیابی تصاویر مبتنی بر چند درخواست«، مجله مهندسی برق دانشگاه تبریز، دوره ۴۷، شماره ۳، صفحه ۸۹۳-۹۰۳، ۱۳۹۶.
[3] X. Li, L. Chen, L. Zhang, F. Lin, and W.-Y. Ma, “Image annotation by large-scale content-based image retrieval,” ACM International Conference on Multimedia, 2006.
[4] X. Rui, M. Li, Z. Li, W.-Y. Ma, and N. Yu, “Bipartite graph reinforcement model for web image annotation,” ACM International Conference on Multimedia, 2007.
[5] M. J. Huiskes and M. S. Lew, “The MIR flickr retrieval evaluation”, ACM International Conference on Multimedia Information retrieval, 2008.
[6] هنگامه دلجویی و امیرمسعود افتخاری مقدم، »حاشیهنویسی خودکار تصویر با استفاده از ارتباط معنایی بین نواحی مبتنی بر تئوری تصمیم چند شرطی«، مجله مهندسی برق دانشگاه تبریز، دوره ۴۲، شماره ۲، صفحه ۵۲-۳۹، ۱۳۹۲.
[7] C. Blake and C. J. Merz, UCI Repository of Machine LearningDatabases,http://mlearn.ics.uci.edu/MLRepository.html, University of California, Irvine, School of Information and Computer Sciences, vol 55. 1998.
[8] T. C. Havens, J. C. Bezdek, C. Leckie, L. O. Hall and M. Palaniswami, “Fuzzy c-means algorithms for very large data,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 6, 2012.
[9] X. Li, T. Uricchio, L. Ballan, M. Bertini, C. G. M. Snoek and A. Del Bimbo, “Socializing the semantic gap: a comparative survey on image tag assignment, refinement, and retrieval,” ACM Computing Surveys (CSUR), vol. 49, no. 1, 2016.
[10] S. Lee, W. De Neve and Y. M. Ro, “Visually weighted neighbor voting for image tag relevance learning,” Multimedia Tools Applications, vol. 72, no. 2, pp. 1363–1386, 2014.
[11] T. Uricchio, L. Ballan, M. Bertini and A. Del Bimbo, “An evaluation of nearest-neighbor methods for tag refinement,” International Conference on Multimedia and Expo (ICME), 2013.
[12] L. Chen, D. Xu, I. W. Tsang and J. Luo, “Tag-based image retrieval improved by augmented features and group-based refinement,” IEEE Transactions on Multimedia, vol. 14, no. 4, pp. 1057–1067, 2012.
[13] G. Zhu, S. Yan and Y. Ma, “Image tag refinement towards low-rank, content-tag prior and error sparsity,” International Conference of Multimedia, pp. 461–470, 2010.
[14] J.Tang, X.Shu, G.J.Qi, Z.Li, M.Wang, S.Yan and R.Jain, “Tri-clustered tensor completion for social-aware image tag refinement,” IEEE Transactions on Pattern Analysis and Machine Intelligence., vol. 39, no. 8, pp. 1662–1674, 2017.
[15] X. Yang and F. Yang, “Completing tags by local learning: a novel image tag completion method based on neighborhood tag vector predictor,” Neural Computing and Applications , vol. 27, no. 8, pp. 2407–2416, 2016.
[16] Z. Feng, S. Feng, R. Jin and A. K. Jain, “Image tag completion by noisy matrix recovery,” European Conference on Computer Vision, pp. 424–438, 2014.
[17] Y. Bengio “Learning deep architectures for AI,” Foundations and Trends in Machine Learning, vol. 2, no. 1, 2009.
[18] S. Lawrence, C. L. Giles, A. C. Tsoi and A. D. Back, “Face recognition: a convolutional neural-network approach,” IEEE Transactions on Neural Networks , vol. 8, no. 1, 1997.
[19] G. E. Hinton, “Deep belief networks,” Scholarpedia, vol. 4, no. 5, 2009.
[20] T. Mikolov, M. Karafiát, L. Burget, J. Cernock and S. Khudanpur, “Recurrent neural network based language model,” Interspeech, vol. 2, pp.3, 2010.
[21] R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” Computer Vision and Pattern Recognition (CVPR), pp. 580-587, 2014.
[22] G. Hinton, L. Deng, D. Yu, G. Dahl, AR .Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, TN. Sainath and B. Kingsbury, “Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,” IEEE Signal Processing Magazine, vol. 29, no. 6, 2012.
[23] R. Collobert and J. Weston, “A unified architecture for natural language processing: deep neural networks with multitask learning,” International Conference on Machine Learning, 2008.
[24] K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” International Conference on Learning Representations arXiv preprint arXiv:1409.1556, 2014.
[25] J. Deng, W. Dong, R. Socher, L. Li, K. Li and L. Fei-Fei, “Imagenet: a large-scale hierarchical image database,” Computer Vision and Pattern Recognition, 2009.
[26] J. C. Dunn, “A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters,” 1973.
[27] V. Schwämmle and O. N. Jensen, “A simple and fast method to determine the parameters for fuzzy c–means cluster analysis,” Bioinformatics, vol. 26, no. 22, 2010.
[28] D. Dembélé and P. Kastner, “Fuzzy c-means method for clustering microarray data,” Bioinformatics, vol. 19, no. 8, 2003.
[29] D. Liu, X.-S. Hua, M. Wang and H.-J. Zhang, “Image retagging,” International Conference on Multimedia, 2010.
[30] X. Li, C. G. M. Snoek and M. Worring, “Learning social tag relevance by neighbor voting,” IEEE Transactions on Multimedia, vol. 11, no. 7, 2009.
[31] T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo and Y. Zheng, “NUS-WIDE: a real-world web image database from national university of Singapore,” ACM International Conference on Image and Video Retrieval, 2009.
[32] Z. Lin, G. Ding, M. Hu, Y. Lin and S. S. Ge, “Image tag completion via dual-view linear sparse reconstructions,” Computer Vision Image Understanding, vol. 124, 2014.
[33] S. Zhu, S. Aloufi and A. El Saddik, “Utilizing image social clues for automated image tagging,” IEEE International Conference on Multimedia and Expo (ICME), 2015.
[34] Y. Guo, Y. Liu, A. Oerlemans, S. Lao, S. Wu and M. S. Lew, “Deep learning for visual understanding: A review,” Neurocomputing, vol. 187, 2016.
[35] NUS-WIDE Homepage, Lab for Media Search, http://lms.comp.nus.edu.sg/research/NUS-WIDE.html, Accessed 07.07.2017.
[36] J. Sang, C. Xu, and J. Liu, “User-aware image tag refinement via ternary semantic analysis,” IEEE Transactions on Multimedia, vol. 14, no. 3, 2012.