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Dataset for Transfer Learning with Convolutional Neural Networks for Hydrological Streamline Delineation study

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modified on 2024-02-25, 17:52

Training, validation, and testing data of LiDAR-derived feature maps for hydrological streamline detection of Rowan County and Covington watersheds acquired from USGS

Funding

Category II: ACES - Accelerating Computing for Emerging Sciences

Directorate for Computer & Information Science & Engineering

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HDR Institute: Geospatial Understanding through an Integrative Discovery Environment

Directorate for Computer & Information Science & Engineering

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