Search results for "Pattern Recognition" - Rhea

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• Lecture 25 - Clustering Algorithms OldKiwi
  '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' Examnple with 6 pattern <math>X_1 , X_2 , \cdots , X_6</math>
  8 KB (1,299 words) - 11:24, 10 June 2013
• Hw2 ECE662 S12
  [[Category:pattern recognition]]
  1 KB (164 words) - 14:25, 30 May 2012
• Parametric Estimators OldKiwi
  ...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 (976 words) - 13:25, 8 March 2012
• Lecture19ECE662S12
  [[Category:pattern recognition]] ...sity estimation technique, along with the k-nearest neighbor (KNN) pattern recognition method. More specifically, we presented a formula for estimating a density
  2 KB (274 words) - 10:34, 22 March 2012
• Lecture 26 - Statistical Clustering Methods OldKiwi
  '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes''' *Assume each pattern <math>x_{i}\in D</math> was drawn from a mixture <math>c</math> underlying
  8 KB (1,214 words) - 11:24, 10 June 2013
• Lecture 27 - Clustering by finding valleys of densities OldKiwi
  [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
  8 KB (1,313 words) - 11:24, 10 June 2013
• Lecture 28 - Final lecture OldKiwi
  [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
  10 KB (1,704 words) - 11:25, 10 June 2013
• Lecture20ECE662S12
  [[Category:pattern recognition]]
  2 KB (269 words) - 03:40, 12 April 2012
• Lecture21ECE662S12
  [[Category:pattern recognition]]
  2 KB (259 words) - 03:57, 12 April 2012
• Hw3 ECE662 S12
  [[Category:pattern recognition]] ==Automatic Pattern Recognition Contest!==
  25 KB (2,524 words) - 07:19, 25 June 2012
• Lecture22ECE662S12
  [[Category:pattern recognition]]
  1 KB (181 words) - 03:57, 12 April 2012
• Lecture23ECE662S12
  [[Category:pattern recognition]]
  1 KB (159 words) - 10:01, 23 April 2012
• Lecture24ECE662S12
  [[Category:pattern recognition]]
  1 KB (146 words) - 04:01, 12 April 2012
• Lecture25ECE662S12
  [[Category:pattern recognition]]
  1 KB (166 words) - 04:02, 12 April 2012
• Lecture26ECE662S12
  [[Category:pattern recognition]]
  1 KB (177 words) - 03:49, 19 April 2012
• Lecture27ECE662S12
  [[Category:pattern recognition]]
  1 KB (181 words) - 03:51, 19 April 2012
• Hw3 discussion ECE662 S12
  ...e best students in the world in one of the coolest field of study, pattern recognition! Which classifier will make a better prediction for this data, SVM, Bayes,
  1 KB (219 words) - 11:33, 20 April 2012
• MLE Examples: Binomial and Poisson Distributions OldKiwi
  [[Category:pattern recognition]]
  2 KB (310 words) - 09:58, 23 April 2012
• MLE Examples: Exponential and Geometric Distributions OldKiwi
  [[Category:pattern recognition]]
  3 KB (446 words) - 10:00, 23 April 2012
• Honors project 1 ECE302S12
  [[Category:Pattern Recognition]] ...ttp://www.amazon.com/Pattern-Classification-2nd-Richard-Duda/dp/0471056693 Pattern Classification 2nd edition] by Duda, Hart and Stork. It is a really good bo
  2 KB (236 words) - 18:36, 12 February 2015
• Introduction To Pattern Recognition and Classification
  [[Category:Pattern recognition]] ...e need to first understand the different components that make up a pattern recognition system. <br>
  4 KB (691 words) - 16:46, 15 February 2013
• ECE662 Pattern Recognition Decision Making Processes Spring2008 sLecture collective
  [[Category:pattern recognition]] '''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
  3 KB (425 words) - 09:59, 4 November 2013
• Course info ECE662 Boutin Spring2010
  [[Category:pattern recognition]]
  847 B (111 words) - 10:50, 10 June 2013
• Slectures
  ...cision_Making_Processes_Spring2008_sLecture_collective|Statistical Pattern Recognition Lecture Notes]], collectively written by the students in Prof. Boutin's cla
  1 KB (196 words) - 05:26, 23 July 2013
• Decision Surfaces OldKiwi
  [[Category:pattern recognition]]
  2 KB (245 words) - 10:43, 10 June 2013
• Textbooks OldKiwi
  [[Category:pattern recognition]] === Introduction to Statistical Pattern Recognition ===
  3 KB (372 words) - 10:39, 10 June 2013
• KNN Algorithm OldKiwi
  [[Category:pattern recognition]]
  5 KB (833 words) - 03:31, 19 April 2013
• Student projects
  **[[Introduction To Pattern Recognition and Classification]]
  3 KB (389 words) - 18:10, 23 February 2015
• 2014 Spring ECE 662 Boutin
  == [[ECE662]]: '''Statistical Pattern Recognition and Decision Making Processes, Spring 2014''' (cross-listed with CS662) == ***[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Va
  10 KB (1,450 words) - 20:50, 2 May 2016
• Slecture template ECE662S14
  [[Category:pattern recognition]]
  1 KB (150 words) - 16:27, 30 April 2014
• Data discussion HW1 ECE662 S14 Boutin
  [[Category:pattern recognition]]
  827 B (131 words) - 03:37, 11 March 2014
• From Bayes Theorem to Pattern Recognition via Bayes Rule
  [[Category:pattern recognition]] '''From Bayes' Theorem to Pattern Recognition via Bayes' Rule''' <br />
  14 KB (2,241 words) - 10:42, 22 January 2015
• Lecture 3 - Bayes Theorem and its Application to Pattern Recognition OldKiwi
  #REDIRECT [[From Bayes Theorem to Pattern Recognition via Bayes Rule]]
  70 B (10 words) - 07:10, 12 February 2014
• Yelp Dataset
  [[Category:pattern recognition]]
  1 KB (212 words) - 03:38, 11 March 2014
• Programming help ECE662S14
  [[Category:pattern recognition]]
  330 B (37 words) - 05:25, 17 February 2014
• Upper Bounds for Bayes Error
  [1]. Duda, Richard O. and Hart, Peter E. and Stork, David G., "Pattern Classication (2nd Edition)," Wiley-Interscience, 2000. ...eering.purdue.edu/~mboutin/ Mireille Boutin], "ECE662: Statistical Pattern Recognition and Decision Making Processes," Purdue University, Spring 2014.
  13 KB (2,062 words) - 10:45, 22 January 2015
• Bayes Rule for 1-dimensional and N-dimensional feature spaces
  [[Category:pattern recognition]] ...widely used for many different kinds of applications, especially, pattern recognition. Due to its simplicity and effectiveness, we can use the method in both dis
  19 KB (3,255 words) - 10:47, 22 January 2015
• SlectureKeehwanECE662Spring14
  [[Category:pattern recognition]] *Mireille Boutin, "ECE662: Statistical Pattern Recognition and Decision Making Processes," Purdue University, Spring 2014.
  3 KB (427 words) - 10:50, 22 January 2015
• PCA
  ...principle components. PCA has found numerous application fields like face recognition, dimension reduction, factor analysis and image compression, etc. Generally ...ed. More importantly, the direction of the eignevector shows a significant pattern in the data set. It's easy to find out that the blue line goes through all
  22 KB (3,459 words) - 10:40, 22 January 2015
• ECE662 Whitening and Coloring Transforms S14 MH
  [[Category:pattern recognition]] ...eering.purdue.edu/~mboutin/ Mireille Boutin], "ECE662: Statistical Pattern Recognition and Decision Making Processes," Purdue University, Spring 2014.
  17 KB (2,603 words) - 10:38, 22 January 2015
• PCA comments
  [[Category:pattern recognition]]
  852 B (120 words) - 16:32, 14 May 2014
• Mle tutorial
  [[Category:pattern recognition]] ...avid G. Stork, Pattern Classification. <br>3. Mimi Boutin, ECE 662 Pattern Recognition Lectures. <br>4. http://people.missouristate.edu/songfengzheng/Teaching/MTH
  25 KB (4,187 words) - 10:49, 22 January 2015
• Slecture template video ECE662S14
  [[Category:pattern recognition]]
  1 KB (211 words) - 05:50, 3 September 2014
• How to generate random n dimensional data from two categories with different priors slecture Minwoong Kim ECE662 Spring 2014
  [[Category:pattern recognition]]
  970 B (139 words) - 10:39, 22 January 2015
• How to generate random data two classes Minwoong Kim review
  [[Category:pattern recognition]]
  3 KB (508 words) - 16:12, 14 May 2014
• Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014
  [[Category:pattern recognition]]
  2 KB (226 words) - 10:45, 22 January 2015
• Bayes Rule Minimize Risk Dennis Lee
  [[Category:pattern recognition]] [1]. K. Fukunaga, ''Introduction to Statistical Pattern Recognition'' (Academic, New York, 1972).
  12 KB (1,810 words) - 10:46, 22 January 2015
• Introduction to local density estimation methods
  [[Category:pattern recognition]] [1] Mireille Boutin, “ECE662: Statistical Pattern Recognition and Decision Making Processes,” Purdue University, Spring 2014<br>[2] htt
  15 KB (2,345 words) - 10:52, 22 January 2015
• Curse of Dimensionality
  [[Category:pattern recognition]] ...ectly use all the pixel intensities in an image as the input to their face recognition algorithm. It's simply because there is too much redundant information in t
  9 KB (1,419 words) - 10:41, 22 January 2015
• Bayes Parameter Estimation
  [[Category:pattern recognition]] [1] Mireille Boutin, "ECE662: Statistical Pattern Recognition and Decision Making Processes," Purdue University, Spring 2014.<br>[2] Carl
  15 KB (2,273 words) - 10:51, 22 January 2015