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(Applicaiton of Neural Network to Color Calibration)
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* [http://www.dsi.unifi.it/ANNPR/CR/23.pdf Probabilistic Neural Network]
 
* [http://www.dsi.unifi.it/ANNPR/CR/23.pdf Probabilistic Neural Network]
 
* An Implementation of Neural Network: [http://www.rgu.ac.uk/files/chapter3%20-%20bp.pdf Back Propagation Algorithm]
 
* An Implementation of Neural Network: [http://www.rgu.ac.uk/files/chapter3%20-%20bp.pdf Back Propagation Algorithm]
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== Application of Neural Networks to Color Calibration ==
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The below is a link to a paper which employs Neural Network in calibrating scanner.
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* [https://ritdml.rit.edu/dspace/bitstream/1850/3035/1/PAndersonArticle04-01-1992.pdf]
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Summary: The sanner calibrtion has largely two procedures, gray balancing and transfrom linear RGB data to device independent XYX data. The purpose of this paper is to improve the performance of transformation from RGB to XYZ. The traditional method to transfrom linear RGB to XYZ is to find 3x3 linear transform matrix by minimizing the perceptual error. The author argue that by using Neural Network more precise transform form linear RGB to XYZ can be achieved, as expected, since Neural Network provide more complex nonlinear transformation from input and output. He measuerd the transform error in perceptually uniform domain, and prove the strength of Neural Network in scanner calibration process.
  
 
[[Category:ECE662]]
 
[[Category:ECE662]]

Revision as of 21:26, 24 April 2008

This page and its subtopics discusses everything about Artificial Neural Networks.

Lectures discussing Artificial Neural Networks: Lecture 13_Old Kiwi and Lecture 14_Old Kiwi

Relevant homework: Homework 2_Old Kiwi

References


Application of Neural Networks to Color Calibration

The below is a link to a paper which employs Neural Network in calibrating scanner.

Summary: The sanner calibrtion has largely two procedures, gray balancing and transfrom linear RGB data to device independent XYX data. The purpose of this paper is to improve the performance of transformation from RGB to XYZ. The traditional method to transfrom linear RGB to XYZ is to find 3x3 linear transform matrix by minimizing the perceptual error. The author argue that by using Neural Network more precise transform form linear RGB to XYZ can be achieved, as expected, since Neural Network provide more complex nonlinear transformation from input and output. He measuerd the transform error in perceptually uniform domain, and prove the strength of Neural Network in scanner calibration process.

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva