Document Type

Thesis

Date of Degree

Fall 2012

Degree Name

MS (Master of Science)

Degree In

Electrical and Computer Engineering

First Advisor

Tom Schnell

Abstract

Image recognition and classification is one of the primary challenges of the machine learning community. Recent advances in learning systems, coupled with hardware developments have enabled general object recognition systems to be learned on home computers with graphics processing units. Presented is a Deep Belief Network engineered using NVIDIA's CUDA programming language for general object recognition tasks.

Keywords

CUDA, Machine Learning, Pattern Recogntion

Pages

vii, 170 pages

Bibliography

Includes bibliographical references (pages 61-62).

Copyright

Copyright 2012 Sean Parker

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