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Pattern Recognition/Classifiers PhD

Pattern Recognition/Classifiers PhD

Different course options

Study mode

Full time

Duration

3 years

Start date

23-SEP-24

Key information
DATA SOURCE : IDP Connect

Qualification type

PhD/DPhil - Doctor of Philosophy

Subject areas

Pattern Recognition

Course type

Research

Course Summary

About This Course

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.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

£4,712

International fees
Course fees for EU and international students

For this course (per year)

£20,000

Entry requirements

A good honours degree or equivalent is required.

University information

Bangor University offers an exceptional experience set amidst the captivating landscapes of North Wales, where courses spanning the arts, humanities, and sciences await. The welcoming, student-centred atmosphere in this vibrant and cultured city, combined with the university's size and friendly nature, are reasons why countless students choose to make Bangor their academic home. Bangor is known for having a relatively low cost of living, and...more