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Explore Search: Deep learning (DL)

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Research
Image shows various maps of Canada and the United States showing geophysical datasets

Deep learning (DL)

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Multi-task deep learning of daily streamflow and water temperature

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Automated deep learning-based point cloud classification on USGS 3DEP lidar data using transformer

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Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

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Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska

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Deep learning detection and recognition of spot elevations on historic topographic maps

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Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

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Weakly supervised spatial deep learning for Earth image segmentation based on imperfect polyline labels

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Deep convolutional neural networks for map-type classification

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Historical maps inform landform cognition in machine learning

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GeoImageNet: A multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

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GeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning

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Assessing the utility of uncrewed aerial system photogrammetrically derived point clouds for land cover classification in the Alaska North Slope

Research
underwater features

Feature extraction

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Evaluation of classified ground points from National Agriculture Imagery program photogrammetrically derived point clouds

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Constructing a large-scale landslide database across heterogeneous environments using task-specific model updates

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Remote sensing-based 3D assessment of landslides: A review of the data, methods, and applications

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A reference landform ontology for automated delineation of depression landforms from DEMs

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The evolution of geospatial reasoning, analytics, and modeling

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Validating the use of object-based image analysis to map commonly-recognized landform features in the United States

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The effect of resolution on terrain feature extraction

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Extensibility of U-net neural network model for hydrographic feature extraction and implications for hydrologic modeling

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Automated extraction of areal extents for GNIS Summit features using the eminence core method

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Generalisation operators

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GeoAI for spatial image processing

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Collage of software mapper tools.

2025 CEGIS Annual Research Meeting

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An attention U-Net model for detection of fine-scale hydrologic streamlines

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Generalization in practice within national mapping agencies

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The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure

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GeoAI in the US Geological Survey for topographic mapping

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