Estimation of diabetic retinopathy with artery/vein classification in retinal images using Artificial Neural Network Leshmi Satheesh M.Tech Student,Dept. of Electronics & Communication Mohandas College of Engineering, Kerala University Trivandrum-695541, Kerala, India Email: leshmi24@gmail.com Abstract—Diabetic retinopathy is the single largest explanation for sight loss and visual impairment in eighteen to sixty five year olds . Damage of blood vessels in the eye and the formation of
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* Lens has fixed local lenth. * Adjust the focal length by varying the distance between the lens and the imaging plane. Human eye: * Distance between the lens and retina is fixed. * Focal length for proper focus obatained by varing the shape of the lense. Question: All the center squares hv exactly the same intensity. However, they appear to the eye to become progressively darker as the background becomes lighter. Why? Other example? Answer: The human visual sy
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in our equations to calculate our values. So we need to convert the numbers into the mean, median, mode, range of values, x, x2 and the standard deviation of the data. Second, we will use the data to construct several graphs, such as a boxplot, histogram, stem and leaf plot and a scatter plot to determine if or how the data is skewed and if there are any outliers. If we identify any outliers we will determine whether these are errors. Third we will use a t-test, Chi squares and binomial approximation
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Part I (Chapters 1 – 11) MBA 611 STATISTICS AND QUANTITATIVE METHODS Part I. A. Review of Basic Statistics (Chapters 1-11) Introduction (Chapter 1) Uncertainty: Decisions are often based on incomplete information from uncertain events. We use statistical methods and statistical analysis to make decisions in uncertain environment. Population: Sample: A population is the complete set of all items in which an investigator is interested. A sample is a subset of population values. & Example:
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Quality Management Systems – An Overview TQM ISO 9000 QS 9000 Lecture Objectives Total Quality Management defined Cost of Quality ISO 9000 and QS 9000 Tools of TQM Evolution of Quality Management Six Sigma Quality Mgmt Systems Taguchi DOE SPC Inspection 1930 1950 1975 1985 1990 1995 2000 What does the term Quality really mean? Quality is the ability of a product or service to consistently meet or exceed customer expectations Historical Summary Artisanship • Closeness of
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answer and upload the entire document to the Assignments link by the due date in the syllabus. This is the only version of the assignment that will be graded. Do not use the matching shown on the Materials tab page for Week 5! 1 Which of the following shapes best represents a normal distribution as it is depicted graphically? A. Square B. Bell C. Triangle D. Star E. Hat For questions 2 through 4, consider the following array of numbers: 5 6 7 7 7 8 8 9 9 9 10 15 19 20 21 2. In the array provided
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answer and upload the entire document to the Assignments link by the due date in the syllabus. This is the only version of the assignment that will be graded. Do not use the matching shown on the Materials tab page for Week 5! 1 Which of the following shapes best represents a normal distribution as it is depicted graphically? A. Square B. Bell C. Triangle D. Star E. Hat For questions 2 through 4, consider the following array of numbers: 5 6 7 7 7 8 8 9 9 9 10 15 19 20 21 2. In the array provided
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Answers Possibly for week 1 Quiz in BUS 308 The correct answer for each question is indicated by a . | ------------------------------------------------- Top of Form | 1 CORRECT | | A random sample is selected so that on each selection from the population every unit remaining in the population has an equal chance of being chosen. | | | A) | True | | | B) | False | | | | | | | | 2 INCORRECT | | Any characteristic of a population unit is called a(n): | | |
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Level:Ratings from 1 to 5 where 1= very unsatisfied, 5= very satisfied and 0= no answer/blank | 1.2. Revised Data. Test for Normal Distribution To proceed with the analysis it is necessary to determine if the data are distributed normally. The Histogram below as well as the Descriptive Statistics (Appendix 1, Table 1b) show that the data distribution is leptokurtic (kurtosis is 2,021) and negatively skewed (skewness -,240). We can determine several outliers (Appendix 1, Table 1c, Table 1d) with
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* CONSTANTS – refer to the fundamental quantities that do not change in value. Fixed costs and acceleration due to gravity are examples of such. * VARIABLES – are quantities that may take anyone of a specified set of values. These set of values can be classified as qualitative (categorical) and quantitative (numerical) variables. * It may also refer to any observable characteristics or attributes of group of objects, individual or events. Those variables having cause – and – effect relationships
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