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MARUTI SUZUKI SEGMENTATION AND SALES TREND


Posted by: seminar class
Created at: Monday 18th of April 2011 04:19:44 AM
Last Edited Or Replied at :Saturday 02nd of February 2013 06:29:07 AM
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Other respondents will refuse to cooperate. Still others will give biased or dishonest answers. Finally, some interviewers will be biased or dishonest. Getting the right respondents is critical. It is important to recognize that not everyone in the sample population will be online.
Step 4:-Analyze the information
The next-to-last step in the process is to extract findings from the collected data. The researcher tabulates the data and develops frequency distributions. Averages and measures of dispersion are computed for the major variables. The researcher will also apply some advanced ..................[:=> Show Contents <=:]



Segmentation of Optical Character Recognition


Posted by: seminar class
Created at: Monday 04th of April 2011 12:40:27 AM
Last Edited Or Replied at :Monday 25th of April 2011 06:09:49 AM
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vnagari is the error in character segmentation. Soft computing has been adopted into the process of character recognition for its ability to create input output mapping with good approximation. The alternative for input/output mapping may be the use of a lookup table that is totally rigid with no room for input variations.
The present Project is an attempt to understand the concept of OCR and thereby propounding a monumental effort towards the establishment of OCR that is capable of recognizing devnagari script.
ABOUT THE DEVANAGARI SCRIPT
Devanagari is used in many Indian lan..................[:=> Show Contents <=:]



Segmentation of Pathological and Healthy tissues with Reduced Weighted vectors using


Posted by: seminar class
Created at: Saturday 02nd of April 2011 01:33:28 AM
Last Edited Or Replied at :Saturday 02nd of April 2011 01:33:28 AM
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ntal and vertical planes. In general MRI images are segmented using a fuzzy C-means clustering technique in order to group close pixels with similar pattern. In this case fuzzy logic reveals effective work, but the proposed algorithm is quite sensitive both to selective features and clusters obtained from MRI scanning. Segmentation of image involves in many techniques which are based on edge detection, region or surface growing, threshold level, classifier such as Hierarchical Self Organizing Map (HSOM), and feature vector clustering or vector quantization. Self organizing has proved to be a v..................[:=> Show Contents <=:]



BLOOD VESSEL ENHANCEMENT AND SEGMENTATION USING WAVELET TRANSFORM


Posted by: science projects buddy
Created at: Tuesday 14th of December 2010 07:40:11 PM
Last Edited Or Replied at :Sunday 04th of August 2013 11:51:43 AM
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st to optimise the use of the wavelet

transforms. The methods tested were:

1. Wavelet transform plus adaptive thresholding,

2. Wavelet transform plus supervised classi´Čüers,

3. Wavelet transform plus pixel probabilities combined with adaptivethresholding.


In addition, we compared two training techniques: training on one or more

complete images, then classifying the remaining images, and training on a win-

dow of the image then classifying the remainder of the same image.

Initially the methods were compared qualitatively, but the best of these methods were selected
..................[:=> Show Contents <=:]



Brain Tumor detection using Color-Based K-means Clustering Segmentationfull report u


Posted by: projectsofme
Created at: Friday 01st of October 2010 12:33:15 AM
Last Edited Or Replied at :Friday 01st of October 2010 12:33:15 AM
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the human soft tissue anatomy. The goal of magnetic resonance (MR) image segmentation is to accurately identify the principal tissue structures in these image volumes. A new unsupervised MR image segmentation method based on self-organizing feature map (SOFM) network is presented. The algorithm includes spatial constraints by using a Markov Random Field (MRF) model. The MRF term introduces the prior distribution with clique potentials and thus improves the segmentation results without having extra data samples in the training set or a complicated network structure. The simulation results demon..................[:=> Show Contents <=:]



automatic transmission in cars full report


Posted by: seminar topics
Created at: Monday 15th of March 2010 08:29:54 PM
Last Edited Or Replied at :Monday 25th of April 2011 02:10:20 AM
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ARUN K.M. PRADEEP S.V.
VI SEMISTER
DEPARTMENT OF MECHANICAL ENGINEERING
BAPUJI INSTITUTE OF ENGINEERING AND TECHNOLOGY
DAVANAGERE-577004


INTRODUCTION
One of the biggest things that has always separated drivers is whether they prefer an automatic transmission (sometimes known as a slushbox, because of the characteristic slushy feel it creates when shifting between gears) or a standard transmission (often called, for more obvious reasons, a stick shift).
There are a number of benefits to the standard transmission, but the prevailing reason that most people get them ..................[:=> Show Contents <=:]



automatic segmentation of pulmonary segments from volumetric chest ct scan


Posted by: Rajakumari
Created at: Friday 12th of March 2010 10:51:02 AM
Last Edited Or Replied at :Saturday 26th of January 2013 06:40:13 AM
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project Report in the automatic segmentatoin of pulmonary segments from volumetric chest ct scan[/fo..................[:=> Show Contents <=:]



Segmentation of Touching Characters in Devanagari


Posted by: computer science technology
Created at: Saturday 23rd of January 2010 08:47:51 AM
Last Edited Or Replied at :Saturday 23rd of January 2010 08:47:51 AM
Segmentation of Touching Characters in Devanagari pdf , Segmentation of Touching Characters in Devanagari ppt, Segmentation of Touching Characters in Devanagari , Devanagari, Characters , Touching, Segmentation , character segmentation in devanagari, offline devanagari character recognition ppt ,
m their neighbours,is used to hypothesize character boxes to betouching character boxes. The recognition rate of85% has been achieved on the segmented touchingcharacters...................[:=> Show Contents <=:]



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