Haim Schweitzer Papers on DiSC'04 Long-Term Learning of Semantic Grouping from Relevance-Feedback Publications Note: Links lead to the DBLP on the Web. Haim Schweitzer Haim Schweitzer, J. W. Bell , F. Wu : Very Fast Template Matching. ECCV (4) 2002 : 358-372 Haim Schweitzer: Computing Content-Plots for Video. ECCV (4) 2002 : 491-501 Haim Schweitzer: Template Matching Approach to Content Based Image Indexing by Low Dimensional Euclidean Embedding. ICCV 2001 : 566-571 Haim Schweitzer: Optimal Eigenfeature Selection by Optimal Image Registration. CVPR 1999 : 1219-1224 Haim Schweitzer: Utilizing Scatter for Pixel Subspace Selection. ICCV 1999 : 1111-1116 Haim Schweitzer: Organizing image databases as visual-content search trees. Image Vision Comput. 17 (7): 501-511 (1999) Haim Schweitzer: Precise induction from statistical data. J. Exp. Theor. Artif. Intell. 11 (2): 185-199 (1999) Haim Schweitzer: Computing Ritz Approximations of Primary Images. ICCV 1998 : 139-144 Haim Schweitzer: Indexing Images by Trees of Visual Content. ICCV 1998 : 582-587 Haim Schweitzer, Janell Straach : Utilizing Moment Invariants and Grobner Bases to Reason about Shapes. Computational Intelligence 14 : 461-474 (1998) Haim Schweitzer: Classification and Reductio-ad-Absurdum Optimality Proofs. AAAI/IAAI 1997 : 88-93 Haim Schweitzer: A Distributed Algorithm for Content Based Indexing of Images by Projections on Ritz Primary Images. Data Min. Knowl. Discov. 1 (4): 375-390 (1997) Haim Schweitzer, Radha Krishnan : Structure from Multiple 2D Affine Correspondences without Camera Calibration. CVPR 1996 : 258-263 Haim Schweitzer, Janell Straach : Utilizing Moment Invariants and Gröbner Bases to Reason About Shapes. IJCAI (1) 1995 : 908-914 Haim Schweitzer: Occam Algorithms for Computing Visual Motion. IEEE Trans. Pattern Anal. Mach. Intell. 17 (11): 1033-1042 (1995) James R. Bergen , Haim Schweitzer: A Probabilistic Algorithm for Computing Hough Transforms. J. Algorithms 12 (4): 639-656 (1991) Haim Schweitzer: Probabilities that Imply Certainties. AAAI 1990 : 665-670 Haim Schweitzer: A Necessary Condition for Learning from Positive Examples. Machine Learning 5 : 101-113 (1990) Haim Schweitzer: Non-Learnable Classes of Boolean Formulae That Are Closer Under Variable Permutation. COLT 1988 : 155-166 1 [ 19 ] 2 [ 4 ] 3 [ 7 ] 4 [ 6 ] [ 10 ] 5 [ 19 ] ©2005 Association for Computing Machinery