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References

1. Timo Ojala, Matti Pietikainen, and Topi Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(7):971-987, 2002.

  • 2. Manik Varma and Andrew Zisserman. Texture classification: Are filter banks necessary? In IEEE computer society conference on Computer vision and pattern recognition, volume 2, pages II—691, 2003.
  • 3. Loris Nanni, Michelangelo Paci, and Sheryl Brahnam. Indirect immunofluorescence image classification using texture descriptors. Expert Syst Appl, 41(5):2463-2471, 2014.
  • 4. Ryusuke Nosaka, Chendra Hadi Suryanto, and Kazuhiro Fukui. Rotation invariant cooccurrence among adjacent lbps. In Computer Vision-ACCV 2012 Workshops, pages 15-25. Springer, 2013.
  • 5. X-H Han, Y-W Chen, and Gang Xu. High-order statistics of weber local descriptors for image representation. IEEE Transactions on Cybernetics, 2014.
  • 6. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In Proc. CVPR, pages 1794-1801, 2009.
  • 7. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained linear coding for image classification. In Proc. CVPR, pages 3360-3367, 2010.
  • 8. Linlin Shen, Jiaming Lin, Shengyin Wu, and Shiqi Yu. Hep-2 image classification using intensity order pooling based features and bag of words. Pattern Recognition, 47(7):2419-2427, 2014.
  • 9. Xiang Xu, Feng Lin, Carol Ng, and Khai Pang Leong. Linear local distance coding for classification of hep-2 staining patterns. In Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on, pages 393-400. IEEE, 2014.
  • 10. Xiang Xu, Feng Lin, Carol Ng, and Khai Pang Leong. Automated classification for hep-2 cells based on linear local distance coding framework. EURASIP Journal on Image and Video Processing, 2015(1):1-13, 2015.
  • 11. G. Iannello, L. Onofri, and P. Soda. A bag of visual words approach for centromere and cytoplasmic staining pattern classification on hep-2 images. In 25th international symposium on Computer-based medical systems, pages 1-6, 2012.
  • 12. O. Boiman, E. Shechtman, and M. Irani. In defense of nearest-neighbor based image classification. In Proc. CVPR, pages 1-8, 2008.
  • 13. Jorge Sanchez, Florent Perronnin, Thomas Mensink, and Jakob Verbeek. Image classification with the fisher vector: Theory and practice. International journal of computer vision, 105(3):222-245, 2013.
  • 14. Tommi Jaakkola, David Haussler, et al. Exploiting generative models in discriminative classifiers. Advances in neural information processing systems, pages 487-493, 1999.
  • 15. Florent Perronnin and Christopher Dance. Fisher kernels on visual vocabularies for image categorization. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1-8, 2007.
  • 16. Timo Ahonen, Abdenour Hadid, and Matti Pietikainen. Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(12):2037-2041, 2006.
  • 17. Zhenhua Guo and David Zhang. A completed modeling of local binary pattern operator for texture classification. IEEE Transactions on Image Processing, 19(6):1657-1663, 2010.
  • 18. Subrahmanyam Murala and QM Jonathan Wu. Local ternary co-occurrence patterns: A new feature descriptor for mri and ct image retrieval. Neurocomputing, 119:399-412, 2013.
  • 19. Ryusuke Nosaka, Yasuhiro Ohkawa, and Kazuhiro Fukui. Feature extraction based on cooccurrence of adjacent local binary patterns. In Advances in Image and Video Technology, pages 82-91. Springer, 2012.
  • 20. Ryusuke Nosaka and Kazuhiro Fukui. Hep-2 cell classification using rotation invariant cooccurrence among local binary patterns. Pattern Recognition, 47(7):2428-2436, 2014.
  • 21. Florent Perronnin, Christopher Dance, Gabriela Csurka, and Marco Bressan. Adapted vocabularies for generic visual categorization. In Computer Vision-ECCV 2006, pages 464-475. Springer, 2006.
  • 22. Arthur P Dempster, Nan M Laird, and Donald B Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society. Series B (Methodological), pages 1-38, 1977.
  • 23. Florent Perronnin, Jorge Sanchez, and Thomas Mensink. Improving the fisher kernel for large- scale image classification. In Computer Vision-ECCV 2010, pages 143-156. Springer, 2010.
  • 24. L. Liu, L. Wang, and X. Liu. In defense of soft-assignment coding. In Proc. ICCV, pages 2486-2493,2011.
  • 25. P Foggia, G Percannella, P Soda, and M Vento. Benchmarking hep-2 cells classification methods. IEEE transactions on medical imaging, 32(10):1878-1889, 2013.
 
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