- Based on slide 20 of the renal physiology I, explain your understanding of the reason GFR does not change when blood pressure changes and explain what causes GFR changes.
- Explain your understanding of Renal Clearance (slide 29) and why is important
- Define or describe Cardiac Output, Renal Fraction, and filtrate and what is the relationship to Glomerular Filtration Rate (GFR).
- Review slide 22 of the renal physiology I lecture and explain the significance of the slide (you can explain the entire slide or explain the parts shown)
- Explain why transport maximum occurs during glucose reabsorption.
A few examples of the many methods and algorithm that can be used within the field of facial recognition are: Geometric Feature Based Methods, Template Based Methods, Correlation Based Methods, Matching, Pursuit Based Methods, Singular Value Decomposition Based Methods, The Dynamic Link, Matching Methods, Illumination Invariant Processing Methods, Support Vector Machine Approach, Karhunen- Loeve Expansion Based Methods, Feature Based Methods, Neural Network Based Algorithms and Model Based Methods . Later on, one of the most known methods will be discussed in a detailed way. The facial recognition methods that can be used, all have a different approach. Some are more frequently used for facial recognition algorithms than others. The use of a method also depends on the needed applications. For instance, surveillance applications may best be served by capturing face images by means of a video camera while image database investigations may require static intensity images taken by a standard camera. Some other applications, such as access to top security domains, may even necessitate the forgoing of the nonintrusive quality of face recognition by requiring the user to stand in front of a 3D scanner or an infrared sensor. Consequently, there can be concluded that there can be made a division of three groups of face recognition techniques, depending on the wanted type of data results, i.e. methods that compare images, methods that look at data from video cameras and methods that deal with other sensory data, like 3D pictures or infrared imagery. All of them can be used in different ways, to prevent crime from happening or recurring. ii. How do these technologies work? As listed above, there exists a long list of methods and algorithms that can be used for facial recognition. Four of them are used frequently and are most known in the literature, i.e. Eigenface Method, Correlation Method, Fisherface Method and the Linear Subspaces Method. But how do>GET ANSWER