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Title: svm classifier codes for feature classification in retinal images using matlab
Page Link: svm classifier codes for feature classification in retinal images using matlab -
Posted By:
Created at: Sunday 26th of March 2017 06:25:21 PM
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Title: LOCAL INFORMATION BASED OVERLAID TEXT DETECTION BY CLASSIFIER FUSION
Page Link: LOCAL INFORMATION BASED OVERLAID TEXT DETECTION BY CLASSIFIER FUSION -
Posted By: seminar class
Created at: Monday 02nd of May 2011 06:53:07 PM
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ABSTRACT
When implemented in hardware, image-processing algorithms
should be robust to memory limitations because some hardware
architectures may not have memory size as large as the whole
frame size. Although this is not generally a problem for low-level
processing, higher-level understanding, such as object detection,
demands novel solutions because the available information may, in
some cases, be very local, e.g., only a partial view of the object
could fit in the available memory size. In this paper, we pr ....etc

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Title: matlab code for mammogram classifications using svm classifier
Page Link: matlab code for mammogram classifications using svm classifier -
Posted By:
Created at: Friday 09th of November 2012 04:17:21 PM
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i need matlab code for classifying mammographic images using svm classifier
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Title: classifier used
Page Link: classifier used -
Posted By:
Created at: Tuesday 30th of July 2013 12:50:20 PM
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Title: CHARACTER RECOGNITION USING NN based on dotnet
Page Link: CHARACTER RECOGNITION USING NN based on dotnet -
Posted By: srinivasskc
Created at: Saturday 03rd of July 2010 10:46:42 AM
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Title: ppt for mobile human airbag system for fall protection using mems sensors and embedded svm classifier
Page Link: ppt for mobile human airbag system for fall protection using mems sensors and embedded svm classifier -
Posted By:
Created at: Wednesday 24th of July 2013 10:19:29 PM
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Title: Image Processing - Optical Character Recognition
Page Link: Image Processing - Optical Character Recognition -
Posted By: nit_cal
Created at: Friday 30th of October 2009 06:13:15 PM
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Abstract
Image Processing is now a days considered to be a favorite topic in the IT industry. One of its major applications is Optical Character Recognition (OCR). When the object to be matched is presented then our brains or in general recognition system starts extracting the important features of the object that includes color, depth, shape & size. These features are stored in the part of the memory. Now the brain starts finding the closest match for these extracted features in the whole collection of objects, which is already stored in it. ....etc

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Title: Implementation of Multilayered Perceptron in Optical Character Recognition using Supe
Page Link: Implementation of Multilayered Perceptron in Optical Character Recognition using Supe -
Posted By: seminar presentation
Created at: Saturday 29th of May 2010 02:49:57 AM
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Neural network mechanisms are a relatively new and developing science in computer technologies. The particular area derives its basis from the way neurons interact and function in the natural animal brain, especially humans. The animal brain is known to operate in massively parallel manner in recognition, reasoning, reaction and damage recovery. All these seemingly sophisticated undertakings are now understood to be attributed to aggregations of very simple algorithms of pattern storage and retrieval. Neurons in the brain communicate with one a ....etc

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Title: source code for number plate recognition with optical character recognition
Page Link: source code for number plate recognition with optical character recognition -
Posted By:
Created at: Tuesday 02nd of May 2017 12:14:43 PM
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Title: Neural Networks for Unicode Optical Character Recognition
Page Link: Neural Networks for Unicode Optical Character Recognition -
Posted By: computer science crazy
Created at: Friday 18th of September 2009 12:57:50 AM
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Neural Networks for Unicode Optical Character Recognition
Abstract: 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 classic difficulty of being able to correctly recognize even typed optical language symbols is the complex irregularity among pictorial representations of the same c ....etc

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