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character recognition using neural network matlab code


Posted by:
Created at: Saturday 27th of October 2012 02:25:08 PM
Last Edited Or Replied at :Monday 29th of October 2012 07:17:03 AM
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i want matlab code for c..................[:=> Show Contents <=:]



CHARACTER RECOGNITION USING ARTIFICIAL NEURAL NETWORK


Posted by: seminar class
Created at: Saturday 30th of April 2011 04:15:17 AM
Last Edited Or Replied at :Saturday 30th of April 2011 04:15:17 AM
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their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. A trained neural network can be thought of as an expert in the category of information it has been given to analyse. This expert can then be used to provide projections given new situations of interest and answer what if questions.
Other advantages include:
1. Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience..................[:=> Show Contents <=:]



CHARACTER RECOGNITION USING NN based on dotnet


Posted by: srinivasskc
Created at: Friday 02nd of July 2010 09:46:42 PM
Last Edited Or Replied at :Friday 02nd of July 2010 09:46:42 PM
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hi...
can any one provide the project on CHARACTER RECOGNITION USING NN based on dotnet ...................[:=> Show Contents <=:]



Combined Economic and Emission Dispatch using RBF neural network


Posted by: computer science topics
Created at: Tuesday 22nd of June 2010 11:05:29 AM
Last Edited Or Replied at :Tuesday 22nd of June 2010 11:05:29 AM
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smallest hi unit until Pi,max = PD
¢ At this stage, hi associated with the last unit in the process is the price penalty factor for the given load.



Modified Price Penalty Factor

¢ The computation steps for hpd :
¢ Find the ratio between maximum fuel cost and maximum emission of each generator
¢ sort hi values in ascending order
¢ Form an array, m by adding Pi,max one by one from the lowest hi value unit
¢ Add the elements of mi one at a time, starting from the smallest hi unit until S m > PD
¢ The modified price penalty factor hpd is computed by inte..................[:=> Show Contents <=:]



Implementation of Multilayered Perceptron in Optical Character Recognition using Supe


Posted by: seminar presentation
Created at: Friday 28th of May 2010 01:49:57 PM
Last Edited Or Replied at :Friday 28th of May 2010 01:49:57 PM
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elligenceâ„¢ tasks believed to be impossible in the pas..................[:=> Show Contents <=:]



Unicode OCR using Artificial Neural Network methods


Posted by: project topics
Created at: Wednesday 21st of April 2010 01:58:11 PM
Last Edited Or Replied at :Wednesday 21st of April 2010 01:58:11 PM
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nicode OCR using Artificial Neural Network methods

This project will recognizes typed latin optical characters and outputs the corresponding Unicode value and character. It is implemented using Artificial Neural Network methods and can be trained for any available font type.

The central objective of this project is demonstrating the capabilities of Artificial Neural Network implementations in recognizing extended sets of optical language symbols. The applications of this technique range from document digitizing and preservation to handwritten text recognition in handheld devices.

The..................[:=> Show Contents <=:]



Image Processing - Optical Character Recognition


Posted by: nit_cal
Created at: Friday 30th of October 2009 05:13:15 AM
Last Edited Or Replied at :Wednesday 09th of March 2011 02:48:36 AM
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the memory. Now the brain starts ..................[:=> Show Contents <=:]



Neural Networks for Handwritten character and Digits


Posted by: computer science crazy
Created at: Thursday 17th of September 2009 11:53:25 AM
Last Edited Or Replied at :Thursday 17th of September 2009 11:53:25 AM
Digits, character , Handwritten, Networks , Neural, handwritten character recognition using convolutional neural networks ,
(a five-layer convolution neural network) built for one very specific purpose (to recognize handwritten digits).
The idea of using neural networks for the purpose of recognizing handwritten digits is not a new one. The inspiration for the architecture described here comes from articles written by two separate authors. The first is Dr. Yann LeCun, who was an independent discoverer of the basic back propagation algorithm. Dr. LeCun hosts an excellent site on his research into neural networks. In particular, you should view his Learning and Visual Perception section, which uses animated GIFs ..................[:=> Show Contents <=:]



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