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An image recognition AI (Artificial Intelligence) software is usually designed with the ability to learn from a huge number of images. Various attributes will be collected and analyzed to find the amount of impact of these attributes. The most impacting attributes will then be used to form a complicated math equation for image recognition purpose. For each attribute, some values could be outliners (outside a normal value range) and would affect the formula negatively. So, the software should be able to recognize them and remove outliners from the learning source. At the end, such complicated math equation can be used to recognize (calculate) an object from an image.
Instructions
Describe, in detail, at least two major logical parts of this problem where you would have to apply pattern recognition (not data representation).
What patterns are revealed and how does this help in providing a better solution to this problem?
Your answers should explore the topics in depth and not be trivial.
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