Abstract

Current research has shown that it is possible to create a general purpose learning system that models the first few layers of the human visual system. The goal of this thesis is to build upon that idea and produce a computational model capable of learning different aspects of visual information. Simulations show that the system is capable of learning and distinguishing different types of motion. Results also give one explanation, consistent with current experiments, explaining how the human visual system learns information and as such may produce the capability to predict behavior in future experiments.

Library of Congress Subject Headings

Motion perception (Vision)--Computer simulation; Visual pathways--Computer simulation; Computer vision

Publication Date

2004

Document Type

Thesis

Student Type

Graduate

Degree Name

Computer Science (MS)

Department, Program, or Center

Computer Science (GCCIS)

Advisor

Roger Gaboski

Advisor/Committee Member

Michael Van Wie

Advisor/Committee Member

Edith Hemaspaandra

Comments

Physical copy available from RIT's Wallace Library at TA1634 .B729 2004

Campus

RIT – Main Campus

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