Create the page "Pattern Recognition" on this wiki! See also the search results found.

  • 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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