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Pattern recognition is a very active field of research intimately bound to machine learning and data mining. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern. An input could be the ZIP code on an envelope, a satellite image, microarray gene expression data, a chemical signature of an oil-field probe, a financial record of a company and many more. The classifier may take a form of a function, an algorithm, a set of rules, etc. Pattern recognition is about training such classi...
Pattern recognition is a very active field of research intimately bound to machine learning and data mining. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern. An input could be the ZIP code on an envelope, a satellite image, microarray gene expression data, a chemical signature of an oil-field probe, a financial record of a company and many more. The classifier may take a form of a function, an algorithm, a set of rules, etc. Pattern recognition is about training such classifiers to do tasks that could be tedious, dangerous, infeasible, impractical, expensive or simply difficult for humans. Pattern recognition faces many challenges in the modern era of massive data collection (e.g. in retail, communication and Internet) and high demand for precision and speed (e.g. in security monitoring and target tracking). New methodologies are needed to answer these application-born challenges.
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Course Details
Information
Study Mode
Full-time
Duration
2 Years
Start Date
09/2024
Campus
Bangor Campus
Application deadline
Provider Details
Codes/info
Course Code
Unknown
Institution Code
B06
Points of Entry
Unknown
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