Pattern Recognition Research Area
(adapted in part from
http://noodle.med.yale.edu/hdtag/v_course/v_course.html)
Area Description
Pattern recognition is the research area that studies
the operation and design of systems that recognize patterns in data. It encloses
subdisciplines like discriminant analysis, feature extraction, error estimation,
cluster analysis (together sometimes called statistical pattern recognition),
grammatical inference and parsing (sometimes called syntactical pattern
recognition). Important application areas are image analysis, character
recognition, speech analysis, man and machine diagnostics, person identification
and industrial inspection.
For a nice overview, see the pages by Duda.
Related Areas
In the following areas closely related systems are studied
or similar tools are developed.
- Artificial Intelligence (expert systems and machine learning)
- Neural Networks
- Vision
- Cog nitive Sciences and Biological Perception
- Mathematical Statistics (hypothesis testing and parameter estimation)
- Nonlinear Optimization
- Exploratory Data Analysis
Click here for a list of
monographs introducing pattern recognition and related fields.