Digital Archaeology: Detection of Archaeological Structures Using Convolutional Neural Networks on Aerial LiDAR Data
Senior Project Advisor
Archaeology, Machine Learning, Computer Science, LiDAR, Semantic Segmentation
Archaeology is a field that is mostly done by hand. Archaeologists explore remote and unknown areas of the world to find undiscovered civilizations that will give us any idea about how people lived in the past. To speed up this process, Airborne light detection and ranging or LiDAR systems have been used to great effect to speed up this processing. However, we still require domain experts to annotate this information to confirm structures. Deep learning has the potential to speed up this process and the following presentation is a basic overview of machine learning, popular types of deep learning models, as well as an exploration into my own project as part of a research group at Western Washington University.
LaRue, Katie, "Digital Archaeology: Detection of Archaeological Structures Using Convolutional Neural Networks on Aerial LiDAR Data" (2023). WWU Honors College Senior Projects. 639.
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