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optical character recognition using neural networks ppt
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Optical Character Recognition Using Neural Networks


Posted by: smart paper boy
Created at: Tuesday 16th of August 2011 04:51:44 AM
Last Edited Or Replied at :Thursday 19th of January 2012 10:33:12 PM
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we try to understand what exactly happens when we are reading, we will realize that when we see the printed paper an image gets formed on the retina of the eye, some signals are sent to the brain and the brain cells called neurons have something called as intelligence due to which they can recognize the characters.
Now, if we simulate this behavior in software, what we would be actually doing is creating artificial intelligence. This filed of artificial intelligence, which simulates the behavior of a biological neural network in order to perform intelligent tasks, is called artificial neural..................[:=> Show Contents <=:]



Digit Recognition using Neural Network


Posted by: Electrical Fan
Created at: Saturday 14th of November 2009 05:33:37 AM
Last Edited Or Replied at :Thursday 19th of January 2012 10:33:35 PM
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ifying numerals efficiently. The neural network will be trained with a database consisting of handwritten digits provided by writers of various ages with many different sizes and writing styles. Numerals poorly drawn or cannot be classified are rejected. A..................[:=> Show Contents <=:]



Face Recognition Using Artificial Neural Networks


Posted by: nit_cal
Created at: Saturday 31st of October 2009 04:58:30 AM
Last Edited Or Replied at :Saturday 20th of April 2013 12:55:41 AM
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solving. Inherent non-linearity property of Neural Networks makes it particularly suitable in many signal-processing applications like sound, image processing

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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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ecognition seems to be simple task but to make a computer analyze and finally correctly recognize a character is a difficult task. Here we are basically dealing with the â„¢Upper Case Characterâ„¢ recognition.
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Neural Networks for Unicode Optical Character Recognition


Posted by: computer science crazy
Created at: Thursday 17th of September 2009 11:57:50 AM
Last Edited Or Replied at :Thursday 20th of October 2011 11:29:03 PM
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ing rules are termed as Supervised Learning.
One such network with supervised learning rule is the Multi-Layer Perceptron (MLP) model. It uses the Generalized Delta Learning Rule for adjusting its weights and can be trained for a set of input/desired output values in a number of iterations. The very nature of this particular model is that it will force the output to one of nearby values if a variation of input is fed to the network that it is not trained for, thus solving the proximity issue. Both concepts will be discussed in the introduction part of this report.The project has employed the ..................[:=> Show Contents <=:]



Emerging Trends In Robotics Downlaod Seminar Report


Posted by: Computer Science Clay
Created at: Thursday 30th of July 2009 06:46:58 AM
Last Edited Or Replied at :Thursday 30th of July 2009 06:46:58 AM
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TURN RIGHT, CONTINUE.

This is a very common ËœIF-THENâ„¢ statement.

A machine that can perform this instruction is truly a robot. So, the conclusion is that to be called a robot; you really need an on-board brain and a way to program it.

Classification of ROBOTS:
Robot like devices:
Prostheses
Exoskeletons
Telecherics
Locomotive mechanism
Classification by coordinate system:
Cylindrical coordinate robots
Spherical coordinate robots
Jointed arm robots
Cartesian coordinate robots
Classification by control method:
Non-servo controlled robots
Servo controlled robots
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Cellular Neural Network


Posted by: Computer Science Clay
Created at: Tuesday 24th of February 2009 12:56:26 PM
Last Edited Or Replied at :Sunday 21st of November 2010 10:46:10 PM
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proven new computing paradigm for analog computers. Looking at the technological advancement in the last 50 years ; we see the first revolution which led to pc industry in 1980's, second revolution led to internet industry in 1990's cheap sensors & mems arrays in desired forms of artificial eyes, nose, ears etc. this third revolution owes due to C.N.N.This technology is implemented using CNN-UM and is also used in imageprocessing.It can also implement any Boolean functions.

ARCHITECTURE OF CNN

A standard CNN architecture consists of an m*n rectangular array of cells c(i,j) with Cartesian..................[:=> Show Contents <=:]



Industrial Applications using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:08:04 AM
Last Edited Or Replied at :Thursday 05th of August 2010 12:43:13 PM
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l to increase the efficiency of process operations. One possible approach for achieving this is through the improvement of existing process monitoring and control systems.Many process monitoring and control schemes are based upon a representation of the dynamic relationship between cause and effect variables. In such schemes, this representation is typically approximated using some form of linear dynamic model, such as finite impulse response (FIR), autoregressive with exogenous variable (ARX) and auto-regressive, moving average with exogeneous variable (ARMAX) models. Once determined, the dyn..................[:=> Show Contents <=:]



Transient Stability Assessment using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:07:56 AM
Last Edited Or Replied at :Tuesday 19th of October 2010 05:02:49 AM
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ations give scope to errors.

The advantages:
1. this technique has the potential of faster transient stability assessment than the other other conventional methods.
2. This technique provides the online transient stability assessment..................[:=> Show Contents <=:]



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