Ten Lectures on Statistical and Structural Pattern Recognition

Preface. Lecture 1. Bayesian statistical decision making. Lecture 2. Non-Bayesian statistical decision making. Lecture 3. Two statistical models of the recognised object. Lecture 4. Learning in pattern recognition. Lecture 5. Linear discriminant function. Lecture 6. Unsupervised Learning. Lecture 7. Mutual relationship of statistical and structural recognition. Lecture 8. Recognition of Markovian sequences. Lecture 9. Regular languages and corresponding pattern recognition tasks. Lecture 10. Context-free languages, their 2-D generalisation, related tasks. Bibliography. Index.

[1]  G H Ball,et al.  A clustering technique for summarizing multivariate data. , 1967, Behavioral science.

[2]  E. S. Pearson,et al.  On the Problem of the Most Efficient Tests of Statistical Hypotheses , 1933 .

[3]  Albert B Novikoff,et al.  ON CONVERGENCE PROOFS FOR PERCEPTRONS , 1963 .

[4]  Monique Pavel,et al.  Fundamentals of pattern recognition , 1989 .

[5]  Jirí Grim,et al.  On numerical evaluation of maximum-likelihood estimates for finite mixtures of distributions , 1982, Kybernetika.

[6]  H. Robbins An Empirical Bayes Approach to Statistics , 1956 .

[7]  Sarunas Raudys,et al.  On Dimensionality, Sample Size, Classification Error, and Complexity of Classification Algorithm in Pattern Recognition , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  J. Andel Sequential Analysis , 2022, The SAGE Encyclopedia of Research Design.

[9]  Isaac Amidror,et al.  The Theory of the Moiré Phenomenon , 2000, Computational Imaging and Vision.

[10]  Stuart E. Dreyfus,et al.  Applied Dynamic Programming , 1965 .

[11]  Tomaso Poggio,et al.  Image Representations for Visual Learning , 1996, Science.

[12]  New York Dover,et al.  ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .

[13]  László Györfi,et al.  A Probabilistic Theory of Pattern Recognition , 1996, Stochastic Modelling and Applied Probability.

[14]  Enrique Vidal,et al.  Two Different Approaches for Cost-Efficient Viterbi Parsing with Error Correction , 1996, SSPR.

[15]  Sergios Theodoridis,et al.  Pattern Recognition , 1998, IEEE Trans. Neural Networks.

[16]  Jerzy Neyman,et al.  Two Breakthroughs in the Theory of Statistical Decision Making , 1962 .

[17]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[18]  C. K. Chow,et al.  Statistical Independence and Threshold Functions , 1965, IEEE Trans. Electron. Comput..

[19]  Noam Chomsky,et al.  Chomsky: Selected readings; , 1971 .

[20]  B. John Oommen Recognition of Noisy Subsequences Using Constrained Edit Distances , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  You-yen. Yang Classification into two multivariate normal distributions with different covariance matrices , 1965 .

[22]  Alfred V. Aho,et al.  The Theory of Parsing, Translation, and Compiling , 1972 .

[23]  Longin Jan Latecki Discrete Representation of Spatial Objects in Computer Vision , 1998, Computational Imaging and Vision.

[24]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[25]  Daniel H. Younger,et al.  Recognition and Parsing of Context-Free Languages in Time n^3 , 1967, Inf. Control..

[26]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[27]  Georgy L. Gimel'farb,et al.  Image Textures and Gibbs Random Fields , 1999, Computational Imaging and Vision.

[28]  J. Wolfowitz,et al.  Optimum Character of the Sequential Probability Ratio Test , 1948 .

[29]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[30]  Tadao Kasami,et al.  An Efficient Recognition and Syntax-Analysis Algorithm for Context-Free Languages , 1965 .

[31]  Franc Solina,et al.  Segmentation and Recovery of Superquadrics , 2000, Computational Imaging and Vision.

[32]  Karl Rohr,et al.  Landmark-Based Image Analysis , 2001, Computational Imaging and Vision.

[33]  Josef Kittler,et al.  Pattern recognition : a statistical approach , 1982 .

[34]  K. X. M. Tzeng,et al.  Convolutional Codes and 'Their Performance in Communication Systems , 1971 .

[35]  Hans-Jürgen Zimmermann,et al.  Fuzzy sets and decision analysis , 1984 .

[36]  H. Robbins Asymptotically Subminimax Solutions of Compound Statistical Decision Problems , 1985 .

[37]  Vladimir Kovalevsky,et al.  Sequential optimization in pattern recognition and pattern description , 1968, IFIP Congress.

[38]  David B. Cooper,et al.  Nonsupervised Adaptive Signal Detection and Pattern Recognition , 1964, Inf. Control..

[39]  K. Schittkowski,et al.  NONLINEAR PROGRAMMING , 2022 .

[40]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[41]  Joel I. Seiferas,et al.  Correcting Counter-Automaton-Recognizable Languages , 1978, SIAM J. Comput..

[42]  Michael J. Fischer,et al.  The String-to-String Correction Problem , 1974, JACM.

[43]  C. N. Liu,et al.  Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.

[44]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[45]  Horst Bunke Structural and Syntactic Pattern Recognition , 1993, Handbook of Pattern Recognition and Computer Vision.

[46]  Nils J. Nilsson,et al.  Learning Machines: Foundations of Trainable Pattern-Classifying Systems , 1965 .

[47]  Morton Nadler,et al.  Pattern recognition engineering , 1993 .

[48]  J. Kruskal On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .

[49]  Gang Xu,et al.  Epipolar Geometry in Stereo, Motion and Object Recognition , 1996, Computational Imaging and Vision.

[50]  E. Lehmann Testing Statistical Hypotheses , 1960 .

[51]  Michail I. Schlesinger Algebraic method for solution of some best matching problems , 1996, TFCV.

[52]  King-Sun Fu,et al.  Syntactic Methods in Pattern Recognition , 1974, IEEE Transactions on Systems, Man, and Cybernetics.

[53]  N. Shor Nondifferentiable Optimization and Polynomial Problems , 1998 .