Improving Cassification Engine in Content based Image Retrieval by Multi-point Queries via Pareto Approach
S. Agarwal, A.K. Verma and N. Dixit, Content based image retrieval using color edge detection and discrete wavelet transform, in International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), IEEE, 2014, 368 – 372.
R. Arandjelovic and A. Zisserman, Multiple queries for large scale specific object retrieval, in British Machine Vision Conference, 2012, 1 – 11.
M. Arevalillo-Herráez, J. Domingo and F. J. Ferri, Combining similarity measures in content-based image retrieval, Pattern Recognition Letters 29 (16) (2008), 2174 – 2181.
G. Beliakov, A. Pradera and T. Calvo, Aggregation functions: a guide for practitioners, Springer (2007).
M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic et al., Query by image and video content: the qbic system, Computer 28 (9) (1995), 23 – 32.
Y. Freund, R. Schapire and N. Abe, A short introduction to boosting, Journal-Japanese Society For Artificial Intelligence 14 (771-780) (1999), 1612.
V. N. Gudivada and V. V. Raghavan, Content based image retrieval systems, Computer 28 (9) (1995), 18 – 22.
P. Hiremath, S. Shivashankar and J. Pujari, Wavelet based features for color texture classification with application to cbir, International Journal of Computer Science and Network Security 6 (9A) (2006), 124 – 133.
S.C. Hoi, R. Jin, J. Zhu and M.R. Lyu, Semi-supervised svm batch mode active learning for image retrieval, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), IEEE (2008), 1 – 7.
K.-J. Hsiao, J. Calder and A.O. Hero, Pareto-depth for multiple-query image retrieval, IEEE Transactions on Image Processing 24 (2) (2015), 583 – 594.
J. Huang, S.R. Kumar, M. Mitra, W.-J. Zhu and R. Zabih, Image indexing using color correlograms, in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE (1997), 762 – 768.
Y. Ishikawa, R. Subramanya and C. Faloutsos, Mindreader: Querying Databases through Multiple Examples, Computer Science Department, p. 551 (1998).
W. Jiang, G. Er and Q. Dai, Boost svm active learning for content-based image retrieval, in Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers (2003), 1585 – 1589.
X. Jin and J. C. French, Improving image retrieval effectiveness via multiple queries, Multimedia Tools and Applications 26 (2) (2005), 221 – 245.
S. Joseph and K. Balakrishnan, Multi-query content based image retrieval system using local binary patterns, International Journal of Computer Applications 17 (7) (2011), 1 – 5.
K. Hirata and T. Katzo, Query by visual example, content based image retrieval, in Advances in Database Technology-EDBT’92, Vol. 580 (A. Pirotte, C. Delobel and G. Gottlob, Eds.) (1992).
D.-H. Kim and C.-W. Chung, Qcluster: relevance feedback using adaptive clustering for contentbased image retrieval, in Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data (2003), 599 – 610.
D.-H. Kim, C.-W. Chung and K. Barnard, Relevance feedback using adaptive clustering for image similarity retrieval, Journal of Systems and Software 78 (1) (2005), 9 – 23.
T.S. Lee, Image representation using 2d gabor wavelets, IEEE Transactions on Pattern Analysis and Machine Intelligence 18 (10) (1996), 959 – 971.
H. Müller, W. Müller, D.M. Squire, S. Marchand-Maillet and T. Pun, Performance evaluation in content-based image retrieval: overview and proposals, Pattern Recognition Letters 22 (5) (2001), 593 – 601.
C.W. Niblack, R. Barber, W. Equitz, M.D. Flickner, E.H. Glasman, D. Petkovic, P. Yanker, C. Faloutsos and G. Taubin, Qbic project: querying images by content, using color, texture, and shape, in IS&T/SPIE’s Symposium on Electronic Imaging: Science and Technology, International Society for Optics and Photonics 1993, 173 – 187.
A. Oliva and A. Torralba, Modeling the shape of the scene: a holistic representation of the spatial envelope, International Journal of Computer Vision 42 (3) (2001), 145 – 175.
K. Porkaew and K. Chakrabarti, Query refinement for multimedia similarity retrieval in mars, in Proceedings of the Seventh ACM International Conference on Multimedia (Part 1) 1999, 235 – 238.
J.J. Rocchio, Relevance feedback in information retrieval, in The Smart Retrieval System - Experiments in Automatic Document Processing, pp. 313 – 323, Englewood Cliffs, NJ: Prentice-Hall (1971)
Y. Rui, T.S. Huang and S.-F. Chang, Image retrieval: Current techniques, promising directions, and open issues, Journal of Visual Communication and Image Representation, 10 (1) (1999), 39 – 62.
Y. Rui, T.S. Huang and S. Mehrotra, Content-based image retrieval with relevance feedback in mars, in IEEE International Conference on Image Processing, 1997, Proceedings, 2, 815 – 818.
Y. Rui, T.S. Huang, S. Mehrotra and M. Ortega, Automatic matching tool selection using relevance feedback in mars, in Proc. of 2nd Int. Conf. on Visual Information Systems, 1997, https://pdfs.semanticscholar.org/a3ee/13fccb363c9e2f03e73fdf0ce5ccb4ae61f8.pdf
Y. Rui, T.S. Huang, M. Ortega and S. Mehrotra, Relevance feedback: a power tool for interactive content-based image retrieval, IEEE Transactions on Circuits and Systems for Video Technology 8 (5) (1998), 644 – 655.
M.A. Stricker and M. Orengo, Similarity of color images, in IS&T/SPIE’s Symposium on Electronic Imaging: Science & Technology, International Society for Optics and Photonics (1995), 381 – 392.
M.J. Swain and D.H. Ballard, Color indexing, International Journal of Computer Vision 7 (1) (1991), 11 – 32.
K. Tieu and P. Viola, Boosting image retrieval, International Journal of Computer Vision 56 (1-2) (2004), 17 – 36.
S. Tong and E. Chang, Support vector machine active learning for image retrieval, in Proceedings of the Ninth ACM International Conference on Multimedia (2001), 107 – 118.
L. Wang, K.L. Chan and Z. Zhang, Bootstrapping svm active learning by incorporating unlabelled images for image retrieval, Proceeding CVPR’03 Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 629 – 634 (2003).
X.-Y. Wang, H.-Y. Yang, Y.-W. Li, W.-Y. Li and J.-W. Chen, A new svm-based active feedback scheme for image retrieval, Engineering Applications of Artificial Intelligence 37 (2015), 43 – 53.
L. Wu, C. Faloutsos, K. Sycara and T.R. Payne, Falcon: Feedback adaptive loop for content-based retrieval, DTIC Document, Tech. Rep. (2000).
J. Yu, J. Lu, Y. Xu, N. Sebe and Q. Tian, Integrating relevance feedback in boosting for content-based image retrieval, in IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, 2007, I – 965.
L. Zhang, F. Lin and B. Zhang, Support vector machine learning for image retrieval, in Proceedings of IEEE 2001 International Conference on Image Processing 2, 721 – 724.
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