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Neural Network Based Noise Identification in DigitalImages
Image noise is unwanted information in an image and can occur at any moment of time such as during image capture, transmission, or processing and it may or may not depend on image content. In order to remove the noise from the noisy image, prior knowledge about the nature of noise must be known otherwise noise removal causes the image blurring. Identifying nature of noise is a challenging problem. Many researchers have proposed their ideas on image noise identification and each of the work has its assumptions, advantages and limitations. In this paper, we proposed a new methodology based on neural network for identifying the different types of noise such as Non Gaussian, Gaussian white, Salt and Pepper and Speckle noise.
Uploaded by ideseditor on 01/16/2013
Digital publication details: 4 pages.

7. Concepts in Probability, Statistics and Stochastic Modelling
Capítulo 7 del libro Water Resources Systems Planning and Management, del Prof. Daniel Loucks.
Uploaded by jhidalgo54 on 08/03/2009
Digital publication details: 62 pages.

McGraw-Hill,.Schaum's Outline of Business Statistics, 4th Edition.[2004.ISBN0071410805]
McGraw-Hill,.Schaum's Outline of Business Statistics, 4th Edition.[2004.ISBN0071410805]
Uploaded by olivertemuco on 05/16/2009
Digital publication details: 421 pages.

Development of a Wearable Mobility Monitoring System
Gaetanne Hache's Master's Thesis.
Uploaded by nbaddour on 05/09/2011
Digital publication details: 177 pages.

Comparative Advantage of Pakistan agricultural sector
Master Thesis for MSc Food and Resource Economics Submitted at ILR University of Bonn Germany
Uploaded by khalilarbi on 07/26/2009
Digital publication details: 107 pages.

Survival manual
Uploaded by kshaatri on 11/21/2012
Digital publication details: 303 pages.
Tags: manual · spss

002 Lantz.pdf
Uploaded by on 06/12/2013
Digital publication details: 13 pages.

Journal of Mechanical Engineering 2011 9
The Strojniški vestnik – Journal of Mechanical Engineering publishes theoretical and practice oriented papaers, dealing with problems of modern technology (power and process engineering, structural and machine design, production engineering mechanism and materials, etc.) It considers activities such as: design, construction, operation, environmental protection, etc. in the field of mechanical engineering and other related branches.
Uploaded by sv-jme on 09/25/2011
Digital publication details: 92 pages.

How RICCI see the distributions?
Come from qqplot, qqnorm, and qqline.
Uploaded by 3614 on 07/20/2011
Digital publication details: 24 pages.
Tags: qqplot · qqline · qqnorm

Equidistance of Likert-Type Scales and Validation of Inferential Methods Using Experiments and...
Likert-type data are often assumed to be equidistant by applied researchers so that they can use parametric methods to analyse the data. Since the equidistance assumption rarely is tested, the validity of parametric analyses of Likert-type data is often unclear. This paper consists of two parts where we deal with this validity problem in two different respects. In the first part, we use an experimental design to show that the perceived distance between scale points on a regular five-point Likert-type scale depends on how the verbal anchors are used. Anchors only at the end points create a relatively larger perceived distance between points near the ends of the scale than in the middle (end-of-scale effect), while anchors at all points create a larger perceived distance between points in the middle of the scale (middle-of-scale effect). Hence, Likert-type scales are generally not perceived as equidistant by subjects. In the second part of the paper, we use Monte Carlo simulations to...
Uploaded by on 06/16/2013
Digital publication details: 13 pages.
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