DOI

10.17077/etd.33i8zf4n

Document Type

Thesis

Date of Degree

Fall 2012

Degree Name

MS (Master of Science)

Degree In

Electrical and Computer Engineering

First Advisor

Schnell, Tom

First Committee Member

Kuhl, Jon

Second Committee Member

Kruger, Anton

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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