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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
  • Test
    [[Category:pattern recognition]] [2] R. O. Duda, P. E. Hart, and D. G. Stork. ''Pattern Classification (2nd Edition)''. Wiley-Interscience, 2000.
    17 KB (2,590 words) - 10:45, 22 January 2015
  • Lecture 9 - Linear Discriminant Functions OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    9 KB (1,341 words) - 11:15, 10 June 2013
  • KenTobinORNLmboutinOct09
    ...y of our programmatic activities is multi-modal image analysis and pattern recognition. MSSE has a strong history in the development of imaging technologies and
    3 KB (507 words) - 08:30, 22 October 2009
  • Image Morphing
    ...representations of image morphing. Morphing of images is based on pattern recognition and co-ordinate transformation(Bilinear transformation).
    2 KB (262 words) - 03:50, 7 December 2009
  • Peer legacy
    *[[Peer_Legacy_ECE662|ECE662: Statistical Pattern Recognition and Decision Making Processes]]
    4 KB (489 words) - 06:24, 24 April 2012
  • 2010 Spring ECE 662 mboutin
    = [[ECE662]]: "Statistical Pattern Recognition and Decision Making Processes", Spring 2010 = *[["Introduction to Statistical Pattern Recognition" by K. Fukunaga OldKiwi]] (This is the main reference)
    4 KB (547 words) - 12:24, 25 June 2010
  • ECE662 topic1 discussions
    ...gating possible models to incorporate existing Computer Vision and Pattern Recognition methods on Object Detection to infer human activity intention. [[User:Yuanl ...hope I could get a comprehensive understanding of the area of Pattern Recognition. --Hengzhou
    8 KB (1,359 words) - 04:54, 6 May 2010
  • OutlineECE662S10
    | 2. What is pattern Recognition
    1 KB (165 words) - 08:55, 22 April 2010
  • Lecture1ECE662S10
    ...e then talked about "[[What_is_Pattern_Recognition_OldKiwi|what is pattern recognition?]]".
    500 B (67 words) - 07:47, 12 April 2010
  • What is Pattern Recognition OldKiwi
    [[Category:pattern recognition]] =What is Pattern Recognition?=
    3 KB (462 words) - 10:41, 10 June 2013
  • Bayes Rate Fallacy: Bayes Rules under Severe Class Imbalance
    ...n on the class imbalance problem has been given by the statistical pattern recognition community, as shown in [2].
    5 KB (694 words) - 12:41, 2 February 2012
  • Support Vector Machines
    ...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 (416 words) - 10:56, 13 April 2010
  • Homework 2 OldKiwi
    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 (761 words) - 10:53, 13 April 2010
  • Decision Theory Glossary ECE662Spring2008
    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 (4,787 words) - 18:21, 22 October 2010
  • Chess
    ...chess playing is an application of "artificial Intelligence" and "Pattern Recognition". ...tern Recognition and decision making processes"]] to learn what is pattern recognition.
    6 KB (983 words) - 22:31, 9 February 2011
  • Maymester Intro to Machine learning 2011
    = [[SA1050|SA 10503]]: Introduction to Machine Learning & Pattern Recognition=
    4 KB (513 words) - 16:07, 4 November 2010
  • SA1050
    = SA 10503: Introduction to Machine Learning & Pattern Recognition= * [[About Pattern Recognition]]
    1 KB (164 words) - 06:47, 18 November 2010
  • ECE
    *[[ECE662|ECE 662]]: "Pattern recognition and Decision Making Processes
    3 KB (380 words) - 18:29, 9 January 2015
  • Machine learning slectures
    ..._Spring2008_sLecture_collective|The Boutin Lectures on Statistical Pattern Recognition, 2010]] ...l_Pattern_recognition_slectures|The Boutin Lectures on Statistical Pattern Recognition, 2014]]
    1 KB (140 words) - 12:14, 27 March 2015
  • West Lafayette Scholastic November2010 Chess Tournament
    *Pattern recognition
    2 KB (218 words) - 06:24, 19 November 2010
  • Lecture1ECE662S12
    ...nts in the class are working in image processing. We noted that in pattern recognition, one always chooses among a 'finite' set of classes, labeled 1,2,... n. (Ho We used a toy problem to illustrate the statistical pattern recognition paradigm. In this toy problem, a game show host is asking a contestant to g
    3 KB (490 words) - 12:30, 23 February 2012
  • 2012 Spring ECE 662 Boutin
    = [[ECE662]]: "Pattern Recognition and Decision Making Processes", Spring 2012 = ...2=sXtX5ecwEdHxoViGqEcGYA A tutorial on support vector machines for pattern recognition]
    4 KB (514 words) - 07:20, 25 June 2012
  • Lecture2ECE662S12
    ...en replaced this flow chart by a more complex one representing the pattern recognition paradigm from an engineering perspective, where the data acquisition and pr
    2 KB (358 words) - 12:30, 23 February 2012
  • Hw1 ECE662 S12
    [[Category:pattern recognition]]
    918 B (134 words) - 13:18, 8 March 2012
  • Hw1 discussion ECE662 S12
    [[Category:pattern recognition]]
    2 KB (320 words) - 12:21, 12 February 2012
  • Lecture 1 - Introduction OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    3 KB (413 words) - 11:17, 10 June 2013
  • Lecture 3 - Bayes classification OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    6 KB (874 words) - 11:17, 10 June 2013
  • Lecture 4 - Bayes Classification OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    8 KB (1,403 words) - 11:17, 10 June 2013
  • Bayes Classification: Experiments and Notes OldKiwi
    [[Category:pattern recognition]]
    5 KB (772 words) - 11:05, 10 June 2013
  • Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    10 KB (1,609 words) - 11:22, 10 June 2013
  • Lecture 17 - Nearest Neighbors Clarification Rule and Metrics OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' * e.g. fingerprint-based recognition
    6 KB (977 words) - 11:22, 10 June 2013
  • Lecture 18 - Nearest Neighbors Clarification Rule and Metrics(Continued) OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    7 KB (1,098 words) - 11:22, 10 June 2013
  • Lecture 6 - Discriminant Functions OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    10 KB (1,604 words) - 11:17, 10 June 2013
  • Lecture 7 - MLE and BPE OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    10 KB (1,472 words) - 11:16, 10 June 2013
  • Lecture 5 - Discriminant Functions OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    6 KB (946 words) - 11:17, 10 June 2013
  • Lecture 8 - MLE, BPE and Linear Discriminant Functions OldKiwi
    [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
    6 KB (833 words) - 11:16, 10 June 2013
  • Lecture 10 - Batch Perceptron and Fisher Linear Discriminant OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    6 KB (813 words) - 11:18, 10 June 2013
  • Lecture 11 - Fischer's Linear Discriminant again OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    6 KB (946 words) - 11:18, 10 June 2013
  • Lecture 12 - Support Vector Machine and Quadratic Optimization Problem OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    8 KB (1,278 words) - 11:19, 10 June 2013
  • Lecture 13 - Kernel function for SVMs and ANNs introduction OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' ...example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological
    9 KB (1,389 words) - 11:19, 10 June 2013
  • Lecture 14 - ANNs, Non-parametric Density Estimation (Parzen Window) OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    13 KB (2,098 words) - 11:21, 10 June 2013
  • Lecture 15 - Parzen Window Method OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    8 KB (1,246 words) - 11:21, 10 June 2013
  • UCI database with versatile categories of data
    UCI database is a versatile body of pattern recognition data with associated literature and analysis.
    730 B (126 words) - 19:14, 7 February 2012
  • UCI Data Set: Data sorted according to categories(Life Sciences, Physical Sciences etc.)
    UCI database is a versatile body of pattern recognition data with associated literature and analysis.
    740 B (127 words) - 19:54, 7 February 2012
  • Lecture 19 - Nearest Neighbor Error Rates OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    6 KB (1,041 words) - 11:22, 10 June 2013
  • Lecture 20 - Density Estimation using Series Expansion and Decision Trees OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    7 KB (1,082 words) - 11:23, 10 June 2013
  • Lecture 21 - Decision Trees(Continued) OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' defined as the "minimum probability that a training pattern is misclassified"
    7 KB (1,055 words) - 11:23, 10 June 2013
  • Lecture 22 - Decision Trees and Clustering OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' * Example of Index: Face Recognition
    6 KB (837 words) - 11:23, 10 June 2013
  • Lecture 23 - Spanning Trees OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    7 KB (1,091 words) - 11:23, 10 June 2013
  • Lecture 24 - Clustering and Hierarchical Clustering OldKiwi
    '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' [[Category:pattern recognition]]
    9 KB (1,276 words) - 11:24, 10 June 2013

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Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood