L. Xu, Enterprise Systems: State-of-the-Art and Future Trends, IEEE Transactions on Industrial Informatics, vol.7, issue.4, pp.630-640, 2011.

L. Xu, Engineering Informatics: State of the Art and Future Trends, Frontiers of Engineering Management, vol.1, issue.3, pp.270-282, 2014.

L. Xu, Enterprise Integration and Information Architectures, pp.978-979, 2015.
DOI : 10.1201/b17156

L. Bulysheva and J. Jones, A Hybrid Model for Image Databases, Proceedings2nd International Conference on Enterprise Systems, vol.2014, 2014.
DOI : 10.1109/es.2014.48

L. Bulysheva, J. Jones, and Z. Bi, A new approach for image databases design, Information Technology and Management, vol.18, issue.2, pp.97-105, 2015.
DOI : 10.1007/s10799-015-0224-6

Y. Liu, D. Zhang, G. Lu, and W. Ma, A survey of content-based image retrieval with high-level semantics, J. Pattern Recognition, vol.40, issue.1, pp.262-282, 2007.

Y. Li, Object and Content Recognition for content-based Image Retrieval, 2005.

Y. Li and G. Shapiro, Object Recognition for content-based Image Retrieval, Lecture Notes in Computer Science, 2004.

A. Oberoi and M. Singh, Content-Based Image Retrieval System for Medical Databases (CBIR-MD)-Lucratively tested on Endoscopy, Dental and Skull Images, IJCSI Int J Comput Sci, vol.9, pp.1694-0814, 2012.

T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithm, 1990.

D. Zhang, X. Lin, and Y. Jia, The Volume Cutting of Three-Dimensional Image Based on B+ Tree, 4th International Conference, 2010.

R. E. Navathe and B. J. Shamkant, Upper Saddle River, Fundamentals of database systems, pp.652-660, 2010.

A. Bulyshev and L. Bulysheva, Modeling segmentation algorithm, Proceedings of the 3 rd World Congress on Software Engineering, pp.5-9, 2012.

L. Bulysheva and A. Bulyshev, Segmentation modeling algorithm: a novel algorithm in data mining, Information Technology and Management, vol.13, issue.4, pp.263-271, 2012.

D. L. Pham, C. Xu, and J. L. Prince, Current methods in medical image segmentation, Annual Review of Biomedical Engineering, vol.2, pp.315-337, 2000.

L. Florack and A. Kuijper, The topological structure of scale-space images, Journal of Mathematical Imaging and Vision, vol.12, issue.1, pp.65-79, 2000.

A. Kumar and N. Kannathasan, A Survey on Data Mining and Pattern Recognition Techniques for Soil Data Mining, IJCSI International Journal of Computer Science Issues, vol.8, issue.3, pp.1694-0814, 2011.

M. R. Zare, Z. Mueen, and W. C. Seng, Automatic medical X-ray image classification using annotation, J Digit Imaging, vol.27, pp.77-89, 2014.

P. Viola and M. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.

H. Rowley, S. Baluja, and T. Kanade, Neural network-based face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.1, 1998.

S. Dowdy and S. Wearden, Statistics for Research, 1983.

S. Dreiseit and L. Ortho-mochado, Logistic regression and artificial neural network classification models: a methodology review, Journal of Biomedical Informatics, vol.35, issue.5-6, pp.352-359, 2002.

C. Bishop, Pattern Recognition and Machine Learning, 2006.

X. Chen, A. Yuille, and S. U. Zhu, Image Parsing: Unifying Segmentation, Detection, and Recognition, International Journal of Computer Vision, vol.63, issue.2, pp.113-140, 2005.

S. Baker and I. Matthews, Lucas-Kanade 20 Years On: A Unifying Framework, International Journal of Computer Vision, vol.56, issue.3, pp.221-255, 2004.

A. Kotov, Indexing of video flow based of face recognition, 2008.

A. Bulyshev, F. Amzajerdian, V. Roback, G. Hines, D. Pierrottet et al., Three-dimensional super-resolution: theory, modeling, and field test results, Applied Optics, vol.53, issue.12, pp.2583-2594, 2014.