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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.
Theus H Aspiras
Primary Advisor's Department
Electrical and Computer Engineering
Stander Symposium poster
"Resolution exploration using Two-Dimensional Deep Learning Architectures for Infrared Data Captures" (2019). Stander Symposium Posters. 1754.