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Description

This project investigates the effectiveness of deep learning architecture as a means of object detection. To determine the accuracy of the developed algorithm, two-dimensional short-wave infrared aerial captures will be used as training data. By analyzing the accuracy of detection rates with varying resolutions, a baseline image quality for accurate detection will begin to emerge.

Publication Date

4-24-2019

Project Designation

Graduate Research

Primary Advisor

Theus H Aspiras

Primary Advisor's Department

Electrical and Computer Engineering

Keywords

Stander Symposium poster

Comments

Presenter: Jonathan Paul Schierl

Resolution exploration using Two-Dimensional Deep Learning Architectures for Infrared Data Captures

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