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Similarity is a crucial issue in Image Retrieval (Iatan and Worring, BioSystems (Under Review), 2016 ), (Nguyen and Worring, J Vis Lang Comput, 19:203–224, 2008 ), (Nguyen and Worring, ACM Trans Multimed Comput Commun Appl, 4(1):1–23, 2008, ), (Nguyen, Worring and Smeulders, Proceedings of the ACM SIGMM International Workshop on Multimedia Information Retrieval, pp. 107–116, 2006 ). It is relevant both for unsupervised clustering (Strong and Gong, Image Vis Comput, 29:774–786, 2011 ), (Chowhan, Int J Comput Electr Eng, 3(5):743–747, 2011 ) and for supervised classification (Hariri, Shokouhi and Mozayani, Iran J Electr Electron Eng, 4(3):79–93, 2008 ).
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I. Iatan and M. Worring. A fuzzy Kwan–Cai neural network for determining image similarity. BioSystems (Under Review), 2016.
G. P. Nguyen and M. Worring. Interactive access to large image collections using similarity-based visualization. Journal of Visual Languages and Computing, 19:203–224, 2008.
G. P. Nguyen and M. Worring. Optimization of interactive visual-similarity-based search. ACM Transactions on Multimedia Computing Communications and Applications, 4 (1):1–23, 2008.
G. P. Nguyen, M. Worring, and A. W. M. Smeulders. Similarity learning via dissimilarity space in CBIR. In Proceedings of the ACM SIGMM International Workshop on Multimedia Information Retrieval, pages 107–116, 2006.
G. Strong and M. Gong. Similarity-based image organization and browsing using multi-resolution self-organizing map. Image and Vision Computing, 29:774–786, 2011.
S.S. Chowhan. Iris recognition using fuzzy min-max neural network. International Journal of Computer and Electrical Engineering, 3 (5):743–747, 2011.
M. Hariri, S.B. Shokouhi, and N. Mozayani. An improved fuzzy neural network for solving uncertainty in pattern classification and identification. Iranian Journal of Electrical & Electronic Engineering, 4 (3):79–93, 2008.
H. K. Kwan and Y. Cai. A fuzzy neural network and its application to pattern recognition. IEEE Trans. on Fuzzy Systems, 2 (3):185–193, 1997.
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. A fuzzy neural network and its application to pattern recognition. IEEE Trans. on Fuzzy Systems, 88:303–338, 2010.
B. Zaka. Theory and applications of similarity detection techniques. http://www.iicm.tugraz.at/thesis/bilal_dissertation.pdf, 2009.
K. Suzuki, H. Yamada, and S. Hashimoto. A similarity-based neural network for facial expression analysis. Pattern Recognition Letters, 28:1104–1111, 2007.
C.M. Hwang, M.S. Yang, W.L. Hung, and M.G. Lee. A similarity measure of intuitionistic fuzzy sets based on the Sugeno integral with its application to pattern recognition. Information Sciences, 189:93–109, 2012.
Y. Chen, E.K. Garcia, M.Y. Gupta, A. Rahimi, and A. Cazzanti. Similarity-based classification: Concepts and algorithms. Journal of Machine Learning Research, 10:747–776, 2009.
S. Wang, Q. Huang, S. Jiang, Q. Tian, and L. Qin. Nearest-neighbor method using multiple neighborhood similarities for social media data mining. Neurocomputing, 2012.
S. Santini and R. Jain. Similarity measures. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21 (9):871–883, 1999.
G.D. Guo, A.N. Jain, and W.Y. Ma. Learning similarity measure for natural image retrieval with relevance feedback. IEEE Transactions on Neural Networks, 13 (4):811–820, 2002.
A. Mellouk and A. Chebira. Machine Learning. InTech, 2009.
T. Mensink, J. Verbeek, F. Perronnin, and G. Csurka. Metric learning for large scale image classification: Generalizing to new classes at near-zero cost. pages 1–14. ECCV - European Conference on Computer Vision, http://hal.inria.fr/docs/00/72/23/13/PDF/mensink12eccv.final.pdf, 2012.
N. A. Chinchor, and Wong P. C. Thomas, J. J., M. G. Christel, and W. Ribarsky. Multimedia analysis + visual analytics = multimedia analytics. Computer Graphics and Applications, IEEE, 30 (5):52–60, 2010.
W. Lin, D. Tao, J. Kacprzyk, Z. Li, E. Izquierdo, and H. Wang. Multimedia Analysis, Processing and Communications. Springer-Verlag Berlin Heidelberg, 2011.
X. Li, C. G. M. Snoek, and M. Worring. Learning tag relevance by neighbor voting for social image retrieval. In Proceedings of the 1st ACM international conference on Multimedia information retrieval, pages 180–187, 2008.
J. Perkiö, A. Tuominen, and P. Myllymäki. Image similarity: From syntax to weak semantics using multimodal features with application to multimedia retrieval. Multimedia Information Networking and Security, 1:213–219, 2009.
A. Huang. Similarity measures for text document clustering. In NZCSRSC, pages 49–56, 2008.
V. Dutt, V. Chadhury, and I. Khan. Different approaches in pattern recognition. Computer Science and Engineering, 1 (2):32–35, 2011.
R.C. Chakraborty. Fundamentals of neural networks. http://www.myreaders.info/html/artificial_intelligence.htm, 2010.
J.K. Basu, D. Bhattacharyya, and T.H. Kim. Use of artificial neural network in pattern recognition. International Journal of Software Engineering and Its Applications, 4 (2):22–34, 2010.
Yu J., Wang M., and Tao D. Semisupervised multiview distance metric learning for cartoon synthesis. IEEE Transactions on Image Processing, 21 (11):4636–4648, 2012.
Yu J., Tao D., and Wang M. Adaptive hypergraph learning and its application in image classification. IEEE Transactions on Image Processing, 21 (7):3262–3272, 2012.
Yu J., Rui Y., Tang Y.Y., and Tao D. High-order distance-based multiview stochastic learning in image classification. IEEE Transactions on Cybernetics, 44 (12):2431–2442, 2014.
V. Neagoe and I. Iatan. A neuro-fuzzy approach to face recognition. In Proceedings of 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI 2002), 14-18 July 2002, Orlando, Florida, XIV, pages 120–125, 2002.
V. E. Neagoe and O. Stǎnǎşilǎ. Pattern Recognition and Neural Networks (in Romanian). Ed. Matrix Rom, Bucharest, 1999.
I. Iatan. Iris recognition by non- parametric techniques. In Proceedings of International Conference Trends and Challenges in Applied Mathematics, June 20-23, Bucharest, pages 220–223, 2007.
A. Krzyzak. Welcome to pattern recognition homepage. Course Web Page: http://www.cs.concordia.ca/~comp473_2/fall2005/Notes.htm, 2005.
F. P. Romero, A. Peralta, A. Soto, J. A. Olivas, and J. Serrano-Guerrero. Fuzzy optimized self-organizing maps and their application to document clustering. Soft Computing, 14:857–867, 2010.
T.N. Yap. Automatic text archiving and retrieval systems using self-organizing kohonen map. In Natural Language Processing Research Symposium, pages 20–24, 2004.
I. Bose and C. Xi. Applying Kohonen vector quantization networks for profiling customers of mobile telecommunication services. In The Tenth Pacific Asia Conference on Information Systems (PACIS 2006), pages 1513–1526, 2006.
M. Ettaouil, Y. Ghanou, K. El Moutaouakil, and M. Lazaar. Image medical compression by a new architecture optimization model for the Kohonen networks. International Journal of Computer Theory and Engineering, 3 (2):204– 210, 2011.
M. Ettaouil and M. Lazaar. Compression of medical images using improved Kohonen algorithm. Special Issue of International Journal of Computer Applications on Software Engineering, Databases and Expert Systems SEDEXS, pages 41– 45, 2012.
M. Lange, D. Nebel, and T. Villmann. Partial Mutual Information for Classification of Gene Expression Data by Learning Vector Quantization, pages 259– 270. Advances in Self-Organizing Maps and Learning Vector Quantization. Springer, 2014.
A.N. Netravali and B.G. Haskell. Digital Pictures: Representation and Compression. Springer, 2012.
V. Neagoe. A neural approach to compression of hyperspectral remote sensing imagery. In B. Reusch, editor, Computational Intelligence, Theory and Applications, International Conference, 7th Fuzzy Days, Dortmund, Germany, October 1-3, 2001, volume 2206 of Lecture Notes in Computer Science, pages 436–449, 2001.
N.A. AL-Allaf Omaima. Codebook enhancement in vector quantization image compression using backpropagation neural network. Journal of Applied Sciences, 11:3152–3160, 2011.
R. Lamba and M. Mittal. Image compression using vector quantization algorithms: A review. International Journal of Advanced Research in Computer Science and Software Engineering, 3 (6):354–358, 2013.
V.E. Neagoe. Pattern recognition and artificial intelligence (in Romanian), lecture notes, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest. 2000.
F.J. Janse van Rensburg, J. Treurnicht, and C.J. Fourie. The use of fourier descriptors for object recognition in robotic assembly. In 5th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering. https://www.academia.edu/754136/The_Use_of_Fourier_Descriptors_for_Object_Recognition_in_Robotic_Assembly, 2006.
R.A. Tuduce. Signal Theory. Bren, Bucharest, 1998.
T. Kohonen. Self-Organizing Maps. Berlin: Springer- Verlag, 1995.
V. E. Neagoe. Concurrent self-organizing maps for automatic face recognition. In Proceedings of the 29th International Conference of the Romanian Technical Military Academy, November 15-16, 2001, Bucharest. Romania, pages 35–40, 2001.
K. E. A. van de Sande, T. Gevers, and C. G. M. Snoek. Evaluating color descriptors for object and scene recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (9):1582–1596, 2010.
M.A. Anjum. Improved Face Recognition using Image Resolution Reduction and Optimization of Feature Vector. PhD thesis, National University of Sciences and Technology (NUST) Rawalpindi Pakistan, 2008.
S. Dhawan and H. Dogra. Feature extraction techniques for face recognition. International Journal of Engineering, Business and Enterprise Applications, 2 (1):1–4, 2012.
I. Iatan. Neuro- Fuzzy Systems for Pattern Recognition (in Romanian). PhD thesis, Faculty of Electronics, Telecommunications and Information Technology- University Politehnica of Bucharest, PhD supervisor: Prof. dr. Victor Neagoe, 2003.
I. Iatan. Unsupervised neural models and their applications for the feature selection and pattern classification (in Romanian). Master’s thesis, Faculty of Mathematics and Computer Science- University of Craiova, PhD supervisor: Prof. dr. Victor Neagoe, June 1998.
- A Fuzzy Kwan–Cai Neural Network for Determining Image Similarity and for the Face Recognition
Iuliana F. Iatan
- Chapter 2
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