9.913-C Pattern Recognition for Machine Vision, Spring 2002
An example of object detection and recognition application. (Image courtesy of Poggio Laboratory, MIT Department of Brain and Cognitive Sciences.)
Highlights of this Course
Classifier networks are used to inspect, sort, identify, and discriminate minute details in biological or machine systems that human beings cannot discern. They are used in everything from inspecting spark plugs to face recognition. Classifier networks are becoming the basis of machine vision systems. The students' projects are designed to give them practical experience, and to ground graduate students in the field so that they are able to perform this type of research. In the
related resources section, there are links that can be explored for a deeper understanding of these types of classifier networks.
Course Description
The course is directed towards advanced undergraduate and beginning graduate students. It will focus on applications of pattern recognition techniques to problems of machine vision.
The topics covered in the course include:
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Overview of problems of machine vision and pattern classification
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Image formation and processing
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Feature extraction from images
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Biological object recognition
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Bayesian decision theory
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Clustering