- 1.Bach, J.R. et al. (1996). Virage image search engine: an open framework for image management. In Storage and Retrieval for Image and Video Databases IV, Proc. SPIE 2670, pp. 76-87.Google Scholar
- 2.Carson, C. et al. (1999). Color- and texture-based image segmentation using EM and its application to image query and classification. Submitted to IEEE Tran. PAMI.Google Scholar
- 3.Corel (1998). http://www, corel, com.Google Scholar
- 4.Deerwester. S. et al. (1990). Indexing by latent semantic analysis. J. of the Am. Soc. for Information Science, 41, pp. 391-407.Google ScholarCross Ref
- 5.Huang, J., Kumar, S.R., & Zabih, R. (1998). An automatic hierarchical image classification scheme. In Proc. of A CM Multimedia'98, pp. 219-228. Google ScholarDigital Library
- 6.Carkey, L.S. & Croft, W.B. (1996). Combining classifiers in text categorization. In Proc. of SIGIR '96, pp. 289-297. Google ScholarDigital Library
- 7.Lewis, D.D. & Ringuette, M. (1994). A comparison of two learning algorithms for text categorization. In Proc. of SIGIR'9$, pp. 81-93.Google Scholar
- 8.Lewis, D.D. (1995). Evaluating and optimizing autonomous text classification systems. In Proc. of SIGIR'95, pp. 246-254. Google ScholarDigital Library
- 9.Lipson, P., Grimson, E., & Sinha, P. (1997). Configuration based scene classification and image indexing. In Proc. of CVPR'97, pp. 1007-1013. Google ScholarDigital Library
- 10.Niblack, W. et al. (1993). The QBIC project: querying images by content using color, textures and shapes. Storage and Retrieval for Image and Video Databases, Proc. SPIE 1908, pp. 13-25.Google Scholar
- 11.Papageorgiou, P.C., Oren, M., Poggio, T.: A general framework for object detection. In Proc. ICCV, pp. 555-562. Google ScholarDigital Library
- 12.Pentland, A., Picard, & R.W., Sclaroff, S. (1995). Photobook: content-based manipulation of image databases. Intl. J. of Computer Vision, 18(3): 233-254. Google ScholarDigital Library
- 13.Ratan, A.L. & Grimson, W.E.L. (1997). Training templates for scene classification using a few examples. In Proc. IEEE Workshop on Content-Based Analysis of Images and Video Libraries, pp. 90-97. Google ScholarDigital Library
- 14.Unser, M. (1995). Texture classification and segmentation using wavelet frames. IEEE Trans. on Image Proc., 4(11): 1549-1560. Google ScholarDigital Library
Index Terms
- Learnable visual keywords for image classification
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