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  • Main Page
    :[[ECE662|ECE662: "Statistical Decision Theory and Pattern Recognition"]]
    2 KB (209 words) - 13:07, 9 September 2022
  • List of Course Wikis
    :[[2016_Spring_ECE_662_Boutin| ECE662: "Pattern Recognition and Decision Making Processes", Prof. Boutin]] :[[2014_Summer_pattern_recognition_Bochum_Boutin|Bochum Statistical Pattern Recognition]]
    13 KB (1,570 words) - 13:53, 7 August 2018
  • 2014 Summer pattern recognition Bochum Boutin
    [[Category:pattern recognitionBochumSummer2014Boutin]] =Statistical Pattern Recognition (Bochum)=
    215 B (24 words) - 01:55, 8 July 2014
  • Meta Course List
    :[[ECE662|ECE662: "Statistical Decision Theory and Pattern Recognition"]] *[[ECE662|ECE 662]]: "Pattern recognition and Decision Making Processes
    4 KB (474 words) - 07:08, 4 November 2013
  • ECE662:BoutinSpring08 Old Kiwi
    [[Category:pattern recognition]] ...he page for the Spring 2008 edition of the course [[ECE662|ECE662: Pattern Recognition and Decision Making processes]].
    6 KB (747 words) - 05:18, 5 April 2013
  • ECE662:Glossary Old Kiwi
    When we present a trained recognition system with an unknown pattern and ask it to classify it, we call that testing. When we present a pattern recognition with a set of classified patterns so that it can learn the characteristics
    31 KB (4,832 words) - 18:13, 22 October 2010
  • Clustering Old Kiwi
    ..."Dynamic Cluster Formation Using Level Set Methods", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 28, NO. 6, JUNE 2006.''' * K. Fukunaga, Introduction to Statistical Pattern Recognition, second ed. Boston Academic Press, 1990.
    8 KB (1,173 words) - 12:41, 26 April 2008
  • Homework 2 Old Kiwi
    d). Serval matlab codes realated to learning, clustering, and pattern classification : It contains lots of pattern recognition algorithms and gives the description and pesudo code of them.
    5 KB (746 words) - 16:33, 17 April 2008
  • Lecture 1 - Introduction Old Kiwi
    == Definition and Examples of Pattern Recognition == Main article: [[What is Pattern Recognition_Old Kiwi]].
    3 KB (468 words) - 08:45, 17 January 2013
  • Lecture 2 - Decision Hypersurfaces Old Kiwi
    ...obtaining an optimum decision tree is another difficult problem in pattern recognition.
    5 KB (737 words) - 08:45, 17 January 2013
  • Lecture 8 - MLE, BPE and Linear Discriminant Functions Old Kiwi
    ...ata. However, large training datasets are typically unavailable in pattern recognition problems. Furthermore, when the dimension of data increases, the complexity (From [["Pattern Classification" by Duda, Hart, and Stork_Old Kiwi|DHS]] Chapter 5)
    5 KB (792 words) - 08:48, 17 January 2013
  • Lecture 13 - Kernel function for SVMs and ANNs introduction Old Kiwi
    ...example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological
    8 KB (1,354 words) - 08:51, 17 January 2013
  • Textbooks Old Kiwi
    === Introduction to Statistical Pattern Recognition === * One of the three classical books on pattern recognition
    3 KB (340 words) - 17:58, 6 March 2008
  • Support Vector Machines Old Kiwi
    ...pdf/burges98tutorial.pdf A Tutorial on Support Vector Machines for Pattern Recognition] ...arAuthor=Pontil%2C+M.%3B+Verri%2C+A. Support Vector Machines for 3D Object Recognition]
    3 KB (366 words) - 08:48, 10 April 2008
  • ECE662:ChangeLog Old Kiwi
    * 2008/04/25 -- Addeda pattern recognition application field in remote sensing ...thored about 3 feature-based automotive [[Feature Extraction_Old Kiwi|lane recognition]].
    10 KB (1,418 words) - 12:21, 28 April 2008
  • What is Pattern Recognition Old Kiwi
    Definition of Pattern Recognition: Pattern Recognition is the art of assigning classes or categories to data. When the computer i
    3 KB (436 words) - 08:43, 10 April 2008
  • Estimation of Classifiability Old Kiwi
    Estimation of classifiability of various Pattern Recognition techniques is needed to compare them against each other and also to select
    1 KB (170 words) - 08:46, 10 April 2008
  • Parametric Estimators Old Kiwi
    ...ating parameters that are the center of a heated debate within the pattern recognition community. These methods are Maximum Likelihood Estimation (MLE) and Bayes
    6 KB (995 words) - 10:39, 20 May 2013
  • Tools Old Kiwi
    ...ver-studio-freeware-wfhucunj.html] - This is a very simple to use pattern recognition tool. The tool uses artificial intelligence techniques like neural networks ...cognition, face recognition, speech recognition, computer vision, and coin recognition.
    2 KB (307 words) - 17:13, 21 April 2008
  • Scilab Old Kiwi
    Here you can find relevant information on how to implement Pattern Recognition projects using Scilab. * Scilab Toolbox especialized on Pattern Recognition -- Presto-Box [http://www.scilab.org/contrib/index_contrib.php?page=display
    3 KB (376 words) - 20:45, 26 March 2008
  • The R Project Old Kiwi
    ...ould focus on the ones related to the several machine learning and pattern recognition techniques related to the course. Please, follow the links below to more in == Pattern recognition related tutorials ==
    2 KB (241 words) - 23:32, 11 March 2008
  • "Pattern Recognition and Neural Networks" by Brian Ripley Old Kiwi
    ...It will be valuable for understanding some of the applications of pattern recognition
    413 B (53 words) - 23:42, 11 March 2008
  • "Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler Old Kiwi
    ...A great reference if you are interested in the mathematics behind pattern recognition
    479 B (60 words) - 23:43, 11 March 2008
  • "Pattern Classification" by Duda, Hart, and Stork Old Kiwi
    One of the three classical books on pattern recognition. A great reference if you are going to be using the algorithms
    395 B (51 words) - 23:45, 11 March 2008
  • "Introduction to Statistical Pattern Recognition" by K. Fukunaga Old Kiwi
    =Official reference for [[ECE662]]: "Pattern Recognition Theory and Decision Making Processes".= ...or the course. A great reference if you are going to be developing pattern recognition algorithms
    917 B (96 words) - 05:06, 25 August 2010
  • Pattern Recognition Journals Old Kiwi
    A set of journals on pattern recognition and related areas is listed. ...tem.c5efb9b8ade9096b8a9ca0108bcd45f3/index.jsp?&pName IEEE Transactions on Pattern Analysis and Machine Intelligence]
    1 KB (178 words) - 11:46, 16 March 2008
  • Pattern Recognition Conferences Old Kiwi
    ===IEEE Pattern Recognition Conferences 2008=== * [http://www.icpr2008.org/ 19th International Conference on Pattern Recognition, Tampa 2008]
    532 B (64 words) - 12:00, 16 March 2008
  • Publications Old Kiwi
    ==== ''A good review paper on Statistical Pattern Recognition:'' ==== ...ang Mao, "Statistical Pattern Recognition: A Review," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, Jan., 2000
    39 KB (5,715 words) - 10:52, 25 April 2008
  • Comparison of MLE and Bayesian Parameter Estimation Old Kiwi
    ...ating parameters that are the center of a heated debate within the pattern recognition community. These methods are Maximum Likelihood Estimation (MLE) and Bayes
    2 KB (287 words) - 10:39, 20 May 2013
  • Applications of Pattern Recognition Old Kiwi
    ...tioning the field, please explain in detail how a specific tool of pattern recognition can be used in research. * automatic speech recognition
    6 KB (905 words) - 12:18, 28 April 2008
  • Gaussian distribution Old Kiwi
    ...variables approximate the normal distribution. So, considering the pattern recognition case, there will be very large set of feature vectors and classes, and inde
    2 KB (247 words) - 08:32, 10 April 2008
  • Scilab - resources related to Scilab Old Kiwi
    Here you can find relevant information on how to implement Pattern Recognition projects using Scilab. ...page=displayContribution&fileID=194 Scilab Toolbox especialized on Pattern Recognition -- Presto-Box]
    3 KB (379 words) - 10:20, 20 March 2008
  • Bayes Decision Rule Old Kiwi
    [[Category:pattern recognition]]
    1 KB (172 words) - 11:08, 10 June 2013
  • Case-based Reasoning Old Kiwi
    ...d achievements, is to help us to have an insight on how we can use pattern recognition techniques for AI. ...e' statements in a C or C++ program. In RBR we are trying to match a given pattern of features to a rule; the 'if' condition. If we find a match, those rules
    6 KB (1,055 words) - 11:14, 7 April 2008
  • Fisher Linear Discriminant Old Kiwi
    ...79/00982904.pdf Two variations on Fisher's linear discriminant for pattern recognition]" is a nice journal article. The paper provides two fast and simple techni ...79/00982904.pdf Two variations on Fisher's linear discriminant for pattern recognition].
    3 KB (475 words) - 18:05, 28 March 2008
  • Image Processing Old Kiwi
    ===Face Recognition=== ...rl=/iel4/5726/15322/00711956.pdf]. Also variants of FLD are used for face recognition such as DiaFLD [http://linkinghub.elsevier.com/retrieve/pii/S09252312060008
    4 KB (549 words) - 14:40, 25 April 2008
  • Curse of Dimensionality Old Kiwi
    [[Category:pattern recognition]]
    831 B (120 words) - 10:57, 10 June 2013
  • Editing technique Old Kiwi
    Reference: Andrew Webb, "Statistical Pattern Recognition" , 2nd, Wiley, 2001.
    2 KB (296 words) - 11:48, 7 April 2008
  • Fuzzy C-means Old Kiwi
    Fuzzy c-means method (Bezdek, 1981) is frequently used in pattern recognition. It is based on minimization of the following objective function, with resp
    1 KB (258 words) - 16:20, 10 April 2008
  • Video Classification - State of the Art Old Kiwi
    Motion Pattern-Based Video Classification and Retrieval video--> audio--> text(speech) recognition-> keywords
    2 KB (222 words) - 12:12, 11 April 2008
  • Spectral Methods Old Kiwi
    ...dimensionality in order to enable a more effective use of several pattern recognition techniques such as clustering algorithms. Here we review the most popular s
    2 KB (238 words) - 10:41, 28 April 2008
  • MDS Old Kiwi
    ...ation of high dimensional data is important in several subareas of pattern recognition including the verification of cluster validity. In order to visualize high
    3 KB (582 words) - 12:55, 21 April 2008
  • Testing Old Kiwi
    When we present a trained recognition system with an unknown pattern and ask it to classify it, we call that testing.
    117 B (21 words) - 23:25, 24 April 2008
  • Training Old Kiwi
    When we present a pattern recognition with a set of classified patterns so that it can learn the characteristics
    145 B (26 words) - 23:27, 24 April 2008
  • Recommendations for nonlinear discrimination methods Old Kiwi
    ...sing non-linear discrimination techniques in the book "Statistical Pattern Recognition" by Andrew Webb. In this page, I will summarize the main points of the reco #Try simple pattern recognition technique (K-nearest neighbor, linear discriminant analysis)first as a base
    2 KB (311 words) - 10:49, 26 April 2008
  • ECE490W:ECE490W Old Kiwi
    ...r the maymester course ECE490W: Introduction to Machine Learning & Pattern Recognition (in Turkey).
    473 B (74 words) - 17:51, 5 May 2008
  • ECE662:ECE662 Old Kiwi
    This is the kiwi page for the course ECE662: Pattern Recognition and Decision Making Processes
    377 B (57 words) - 18:05, 5 May 2008
  • Lecture 2 - Decision Hypersurfaces OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    5 KB (744 words) - 11:17, 10 June 2013
  • ECE662:BoutinSpring08 OldKiwi
    ...he page for the Spring 2008 edition of the course [[ECE662|ECE662: Pattern Recognition and Decision Making processes]]. * [[What is Pattern Recognition_OldKiwi|What is Pattern Recognition]]
    7 KB (875 words) - 07:11, 13 February 2012
  • ECE662
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    3 KB (429 words) - 09:07, 11 January 2016

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Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva