Machine Learning for GIS and Remote Sensing
This course introduces the theory and applications of both statistical and deep learning-based machine learning methods for supervised learning tasks such as classification, segmentation, object detection, anomaly detection, and change detection for remote sensing data.
Selected Student Projects
Fall 2023
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Solar Radiation’s importance on Air Quality by Victor Geiser
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A Decade of Evolution in STL by Bishal Roy
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An Analysis of Air pollutants and respiratory diseases in California by Imran Said
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The City Above the Mines: Development Dynamics in St. Clair by Cagri Gul
Fall 2022
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Predicting Atmospheric River Conditions along the West Coast by Ryan Kelly
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Predicting Health Inspection Scores in Las Vegas, NV by Alexander Lamb
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How do you systematically prevent Land Encroachment? by Varun Venkatesh