Pattern Recognition
Books
Bibliograpgy
AIZERMAN, M.A., E.M. BRAVERMAN and L. ROZONOER, 1964. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Remote Control. [Cited by 210 ]
AYACHE, N. and O.D. FAUGERAS, 1986. HYPER: A new approach for the recognition and positioning of two-dimensional objects. . IEEE TRANS. PATTERN ANAL. MACH. INTELLIG. [Cited by 174 ]
BASSEVILLE, M., 1988. Distance measures for signal processing and pattern recognition. [Cited by 124 ]
BELKASIM, S.O., M. SHRIDHAR and M. AHMADI, 1991. Pattern recognition with moment invariants: A comparative study and new results. . PATTERN RECOG. [Cited by 103 ]
BEZDEK, J.C. and S.K. PAL, 1992. Fuzzy Models for Pattern Recognition. IEEE, Piscataw ay, NJ. [Cited by 253 ]
BEZDEK, J.C. and S.K. PAL, 1992. Fuzzy models for pattern recognition: methods that search for structures in data. New York: Institute of Electrical and Electronics Engineers. [Cited by 100 ]
BEZDEK, J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms . New York. [Cited by 1668 ]
BEZDEK, J.C., 1981. Pattern Recognition with Fuzzy Objective Function. Plenum, New York NY. [Cited by 120 ]
BEZDEK, J.C., et al. , 2005. Fuzzy models and algorithms for pattern recognition and image processing. New York: Springer. [Cited by 156 ]
BEZDEK, J.C., L.O. HALL and L.P. CLARKE, 1993. Review of MR image segmentation techniques using pattern recognition . Med. Phys. [Cited by 90 ]
BISHOP, C. and C. BISHOP, 1997. Neural Networks for Pattern Recognition . print.google.com. [Cited by 5274 ]
BISHOP, C.M., ISBN. Neural Network for Pattern Recognition. Clarendon Press, Oxford. [Cited by 117 ]
BORGEFORS, G., 1986. Distance transformations in digital images . Computer Vision, Graphics, and Image Processing. [Cited by 419 ]
BRIDLE, J.S., 1990. … of feedforward classification network outputs, with relationships to statistical pattern recognition. Neurocomputing: Algorithms, Architectures and Applications. [Cited by 212 ]
BURGES, C.J.C., 1998. A Tutorial on Support Vector Machines for Pattern Recognition . Data Mining and Knowledge Discovery. [Cited by 1553 ]
CARPENTER, G.A. and S. GROSSBERG, 1987. A massively parallel architecture for a self-organizing neural pattern recognition machine . Computer Vision, Graphics, and Image Processing. [Cited by 633 ]
CARPENTER, G.A. and S. GROSSBERG, 1988. The ART of adaptive pattern recognition by a self-organizing neural network . Computer. [Cited by 291 ]
CARPENTER, G.A. and S. GROSSBERG, 1990. ART3: Hierarchical search using chemical transmitters in self-organizing pattern recognition … . Neural Networks. [Cited by 113 ]
CARPENTER, G.A., et al. , 1991. Pattern recognition by self-organizing neural networks. Cambridge, Mass.: MIT Press. [Cited by 147 ]
DEVIJVER, P.A. and J. KITTLER, 1982. Pattern recognition: a statistical approach. Englewood Cliffs, NJ: Prentice/Hall International. [Cited by 737 ]
DEVROYE, L., L. GYOERFI and G. LUGOSI, 1996. A probabilistic theory of pattern recognition . print.google.com. [Cited by 705 ]
DILL, M., R. WOLF and M. HEISENBERG, 1993. Visual pattern recognition in Drosophila involves retinotopic matching . Nature. [Cited by 59 ]
DUDA, R.O., P.E. HART and D.G. STORK, 1973. Pattern Recognition and Scene Analysis. New York: John Willey. [Cited by 171 ]
DUDA, R.O., P.E. HART and D.G. STORK, 2001. Pattern classification. New York: Wiley. [Cited by 7801 ]
FLUSSER, J. and T. SUK, 1993. Pattern recognition by affine moment invariants. Pattern Recognition. [Cited by 96 ]
FORREST, S., et al. , 1993. Using genetic algorithms to explore pattern recognition in the immune system . Evolutionary Computation. [Cited by 102 ]
FRASER, I.P., H. KOZIEL and R.A. EZEKOWITZ, 1998. … -binding protein and the macrophage mannose receptor are pattern recognition molecules that link … . Semin Immunol. [Cited by 70 ]
FU, K.S. and S. KING, 1974. Syntactic methods in pattern recognition . portal.acm.org. [Cited by 144 ]
FU, K.S., 1982. Syntactic pattern recognition and applications. Englewood Cliffs, NJ: Prentice-Hall. [Cited by 336 ]
FUKUNAGA, K., 1990. Introduction to statistical pattern recognition. Boston: Academic Press. [Cited by 2787 ]
FUKUNAGA, K., 1993. Statistical pattern recognition . Handbook of pattern recognition & computer vision table of …. [Cited by 358 ]
FUKUSHIMA, K. and S. MIYAKE, 1982. Neocognitron: a new algorithm for pattern recognition tolerant of deformations and shifts in … . PATTERN RECOG. [Cited by 102 ]
FUKUSHIMA, K., 1980. … : A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift … . Biological Cybernetics. [Cited by 223 ]
FUKUSHIMA, K., S. MIYAKE and T. ITO, 1988. Neocognitron: a neural network model for a mechanism of visual pattern recognition . Computer Society Press Technology Series Neural Networks. [Cited by 135 ]
FUKUSHIMA, K., S. MIYAKE and T. ITO, 1988. Neocognitron: A hierarchical neural network capable of visual pattern recognition. . Neural Networks. [Cited by 147 ]
GALAS, D.J., M. EGGERT and M.S. WATERMAN, 1985. Rigorous pattern-recognition methods for DNA sequences. Analysis of promoter sequences from … . Journal of Molecular Biology. [Cited by 80 ]
GORDON, S., 2002. Pattern recognition receptors: doubling up for the innate immune response . Cell. [Cited by 114 ]
GOSE, E., R. JOHNSONBAUGH and S. JOST, 1996. Pattern recognition and image analysis. Upper Saddle River, NJ: Prentice Hall PTR. [Cited by 109 ]
GRIMSON, W.E.L., T. LOZANO-PEREZ and D.P. HUTTENLOCHER, 1991. Object Recognition by Computer: The Role of Geometric Constraints. MIT Press. [Cited by 302 ]
HAYKIN, S.S. and S. SIMON, 1999. Neural networks: a comprehensive foundation . cis.hut.fi. [Cited by 4911 ]
HESTER, C.F. and D. CASASENT, 1980. Multivariant technique for multiclass pattern recognition . Appl. Opt. [Cited by 114 ]
HOPFIELD, J.J., 1995. Pattern recognition computation using action potential timing for stimulus representation . Nature. [Cited by 327 ]
HORNER, J.L. and J.R. LEGER, 1985. Pattern recognition with binary phase-only filters . Applied Optics. [Cited by 110 ]
HSU, Y.N., H.H. ARSENAULT and G. APRIL, 1982. Rotation-invariant digital pattern recognition using circular harmonic expansion . Applied Optics. [Cited by 164 ]
HU, M.K., 1962. Visual pattern recognition by moment invariants . Information Theory, IEEE Transactions on. [Cited by 858 ]
ILLINGWORTH, J. and J. KITTLER, 1988. A survey of the Hough transform . Computer Vision, Graphics, and Image Processing. [Cited by 394 ]
JAIN, A.K. and B. CHANDRASEKARAN, 1982. Dimensionality and sample size considerations in pattern recognition practice. Handbook of Statistics. [Cited by 117 ]
JAIN, A.K. and F. FARROKHNIA, 1991. Unsupervised texture segmentation using Gabor filters. . PATTERN RECOG. [Cited by 474 ]
JAIN, A.K., et al. , 2000. Statistical pattern recognition: A review . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 614 ]
JAIN, R., et al. , 1995. Machine Vision . Mcgraw-Hill Series In Computer Science. [Cited by 552 ]
JAVIDI, B. and J.L. HORNER, 2003. Optical pattern recognition for validation and security verification . Proceedings of SPIE. [Cited by 78 ]
KABSCH, W. and C. SANDER, 1983. Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical … . Biopolymers. [Cited by 1673 ]
KOHONEN, T., G. BARNA and R. CHRISLEY, 1988. Statistical pattern recognition with neural networks: Benchmarking studies . IEEE International Conference on Neural Networks. [Cited by 141 ]
KRIEGER, M., 1997. The other side of scavenger receptors: pattern recognition for host defense . Curr Opin Lipidol. [Cited by 97 ]
KURT-JONES, E.A., et al. , 2000. Pattern recognition receptors TLR4 and CD14 mediate response to respiratory syncytial virus . Nat. Immunol. [Cited by 251 ]
LADES, M., et al. , 1993. Distortion invariant object recognition in the dynamic link architecture . IEEE Transactions on Computers. [Cited by 524 ]
LAM, L. and S.Y. SUEN, 1997. Application of majority voting to pattern recognition: an analysis of its behavior and performance . IEEE Transactions on Systems Man and Cybernetics- Part A …. [Cited by 111 ]
LIEN, E., et al. , 1999. Toll-like Receptor 2 Functions as a Pattern Recognition Receptor for Diverse Bacterial Products . Journal of Biological Chemistry. [Cited by 305 ]
LITTLE, R.J.A. and D.B. RUBIN, 1987. Statistical Analysis with Missing Data . New York. [Cited by 2206 ]
LOONEY, C.G., 1997. Pattern Recognition Using Neural Networks. [Cited by 101 ]
MCLACHLAN, G., 1992. Discriminant Analysis and Statistical Pattern Recognition . print.google.com. [Cited by 523 ]
MICHALSKI, R.S., 1980. Pattern recognition as rule-guided inductive inference. IEEE Transactions on Pattern Analysis and Machine …. [Cited by 99 ]
MOGHADDAM, B. and A. PENTLAND, 1997. Probabilistic visual learning for object representation . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 483 ]
NABNEY, I., 2001. NETLAB: algorithms for pattern recognition. New York: Springer. [Cited by 101 ]
NADLER, M. and E.P. SMITH, 1993. Pattern recognition engineering. New York: Wiley. [Cited by 127 ]
OJA, E., 1983. Subspace methods of pattern recognition. Letchworth, Hertfordshire, England: New York: Research …. [Cited by 273 ]
OLSHAUSEN, B.A., C.H. ANDERSON and D.C. VAN, 1993. A neurobiological model of visual attention and invariant pattern recognition based on dynamic … . J. Neurosci. [Cited by 236 ]
OZINSKY, A., et al. , 2005. The repertoire for pattern recognition of pathogens by the innate immune system is defined by … . J. Immunol. [Cited by 422 ]
PAL, S.K., D.D. MAJUMDER and K. DWIJESH, 1986. Fuzzy mathematical approach to pattern recognition. New Delhi: Wiley Eastern. [Cited by 105 ]
PAO, Y.H., 1989. Adaptive Pattern Recognition and Neural Networks. . [Cited by 567 ]
PAVLIDIS, T., 1977. Structural Pattern Recognition. Springer-Verlag. [Cited by 255 ]
PERSOON, E. and K.S. FU, 1986. Shape discrimination using Fourier descriptors . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 255 ]
PLAMONDON, R. and S.N. SRIHARI, 2000. On-line and off-line handwriting recognition: A comprehensive survey . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 186 ]
PLATT, J., 1999. Fast training of support vector machines using sequential minimal optimization . Advances in kernel methods: support vector learning table of …. [Cited by 516 ]
PUDIL, P., J. NOVOVICOVA and J. KITTLER, 1994. Floating search methods in feature selection . Pattern Recognition Letters. [Cited by 272 ]
PUGIN, J., et al. , 1994. CD 14 is a pattern recognition receptor . Immunity. [Cited by 264 ]
RABINER, L., B.H. JUANG and B. JUANG, 1993. Fundamentals of Speech Recognition. Prentice Hall. [Cited by 1973 ]
RAUDYS, S.J. and A.K. JAIN, 1991. Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 154 ]
RECOGNITION, P., 1995. PLANAR SURFACE ORIENTATION FROM TEXTURE SPATIAL FREQUENCIES . Pattern Recognition. [Cited by 38 ]
RECOGNITION, P., 1997. FAST ALGORITHM FOR POINT PATTERN MATCHING: INVARIANT TO TRANSLATIONS, ROTATIONS AND SCALE CHANGES . Pattern Recognition. [Cited by 35 ]
REED, S.K., 1972. Pattern recognition and categorization. Cognitive Psychology. [Cited by 149 ]
RIPLEY, B.D. and N.L. HJORT, 1996. Pattern Recognition and Neural Networks . print.google.com. [Cited by 1566 ]
SAHOO, P.K., et al. , 1988. A survey of thresholding techniques . Computer Vision, Graphics, and Image Processing. [Cited by 371 ]
SAMAL, A. and P.A. IYENGAR, 1992. Automatic Recognition and Analysis of Human Faces and Facial Expressions: A Survey . Pattern Recognition. [Cited by 258 ]
SANFELIU, A., 1980. Distance between attributed relational graphs for pattern recognition. [Cited by 133 ]
SCHALKOFF, R.J., 1992. Pattern recognition: statistical, structural, and neural approaches. New York: J. Wiley. [Cited by 375 ]
SELLERS, P.H., 1980. The Theory and Computation of Evolutionary Distances: Pattern Recognition. J. Algorithms. [Cited by 152 ]
SIMARD, P., Y. LECUN and J.S. DENKER, 1992. Efficient Pattern Recognition Using a New Transformation Distance . Advances in Neural Information Processing Systems 5,[NIPS …. [Cited by 201 ]
STAHL, P.D. and R.A. EZEKOWITZ, 1998. The mannose receptor is a pattern recognition receptor involved in host defense . Curr. Opin. Immunol. [Cited by 179 ]
THEODORIDIS, S., et al. , 1998. Pattern Recognition. Academic Press. [Cited by 465 ]
THERRIEN, C.W., 1989. Decision, estimation, and classification: an introduction to pattern recognition and related topics. New York: Wiley. [Cited by 80 ]
TOU, J.T. and R.C. GONZALEZ, 1974. Pattern recognition principles. Reading, Mass., Addison-Wesley Pub. Co. [Cited by 709 ]
VAPNIK, V. and A. CHERVONENKIS, 1974. Theory of Pattern Recognition. [Cited by 115 ]
WATANABE, S., 1985. Pattern recognition: human and mechanical. New York: Wiley. [Cited by 118 ]
WEBB, A., 1999. Statistical Pattern Recognition . print.google.com. [Cited by 234 ]
WEISS, S.M. and I. KAPOULEAS, 1989. An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification …. IJCAI. [Cited by 160 ]
WESTON, J. and C. WATKINS, 1999. Support vector machines for multi-class pattern recognition . Proceedings of the Seventh European Symposium On Artificial …. [Cited by 79 ]
WIDROW, B., R.G. WINTER and R.A. BAXTER, 1988. Layered neural nets for pattern recognition. . Acoustics, Speech, and Signal Processing [see also IEEE …. [Cited by 64 ]
WOOD, J., 1996. Invariant pattern recognition: a review . Pattern Recognition. [Cited by 82 ]
YOUNG, T.Y., K.S. FU and R. NEVATIA, 1986. Handbook of pattern recognition and image processing. San Diego, Academic Press. [Cited by 84 ]