Learning non-redundant codebooks for classifying complex objects
暂无分享,去创建一个
[1] Naftali Tishby,et al. The Power of Word Clusters for Text Classification , 2006 .
[2] Thomas G. Dietterich,et al. Solving the Multiple Instance Problem with Axis-Parallel Rectangles , 1997, Artif. Intell..
[3] Frédéric Jurie,et al. Fast Discriminative Visual Codebooks using Randomized Clustering Forests , 2006, NIPS.
[4] Thomas G. Dietterich,et al. Principal Curvature-Based Region Detector for Object Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[5] Naftali Tishby,et al. Unsupervised document classification using sequential information maximization , 2002, SIGIR '02.
[6] Gabriela Csurka,et al. Adapted Vocabularies for Generic Visual Categorization , 2006, ECCV.
[7] Andrew McCallum,et al. Distributional clustering of words for text classification , 1998, SIGIR '98.
[8] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[9] Gerard Salton,et al. Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..
[10] Rong Jin,et al. Unifying discriminative visual codebook generation with classifier training for object category recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[11] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[12] Thomas G. Dietterich,et al. Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).
[13] Inderjit S. Dhillon,et al. Simultaneous Unsupervised Learning of Disparate Clusterings , 2008, Stat. Anal. Data Min..
[14] Jiri Matas,et al. Weighted Sampling for Large-Scale Boosting , 2008, BMVC.
[15] Paul A. Viola,et al. Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[16] Inderjit S. Dhillon,et al. A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification , 2003, J. Mach. Learn. Res..
[17] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[18] Andrew Zisserman,et al. An Affine Invariant Salient Region Detector , 2004, ECCV.
[19] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[20] Thomas G. Dietterich. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms , 1998, Neural Computation.
[21] Ying Cui,et al. Non-redundant Multi-view Clustering via Orthogonalization , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[22] Ran El-Yaniv,et al. Distributional Word Clusters vs. Words for Text Categorization , 2003, J. Mach. Learn. Res..
[23] C. Schmid,et al. Object Class Recognition Using Discriminative Local Features , 2005 .
[24] Gal Chechik,et al. Extracting Relevant Structures with Side Information , 2002, NIPS.
[25] Frédéric Jurie,et al. Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[26] Antonio Criminisi,et al. Object categorization by learned universal visual dictionary , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[27] Cordelia Schmid,et al. Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.
[28] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[29] Peter Auer,et al. Generic object recognition with boosting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Thomas G. Dietterich,et al. Automated Insect Identification through Concatenated Histograms of Local Appearance Features , 2007, WACV.
[31] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.