SUPER RESOLVED SATELLITE IMAGES VIA PHYSICS CONSTRAINED NEURAL NETWORK

    公开(公告)号:US20240005065A1

    公开(公告)日:2024-01-04

    申请号:US17809562

    申请日:2022-06-29

    CPC classification number: G06F30/27 G06V10/44

    Abstract: A method, computer program product and system to generate higher resolution geospatial images is provided. A processor receives time sequenced spatial data images at a first resolution. A processor determines from the plurality of spatial data images physics laws applicable to the spatial data images. A processor subdivides each of the plurality of spatial data images into a plurality of small spatial region images. A processor solves each of the physics laws in each of the small spatial region images. A processor trains a neural network to apply each of the physics laws to each small spatial region image by applying a regional physics law loss function. A processor determines the most applicable regional physics law based on the difference between the small spatial region image and the image predicted for that region by the physics law. A processor generates a second higher-resolution image than the first resolution.

    DETECTING GAS LEAKS USING UNMANNED AERIAL VEHICLES

    公开(公告)号:US20180292374A1

    公开(公告)日:2018-10-11

    申请号:US15479325

    申请日:2017-04-05

    Abstract: Methods, systems and computer program products for detecting gas leaks using a drone are provided. Aspects include capturing a first set of data regarding a presence of a gas in the geographic area while flying along the initial flight path. Aspects also include creating secondary flight paths through regions in the geographic area in which the presence of the gas exceeds a threshold amount and capturing a second set of data regarding a concentration of the gas in the one or more regions while flying along the secondary flight paths. Aspects further include capturing wind data while flying along the initial and second flight paths and creating a three-dimensional gas plume model for gas leaks identified in the geographic area based on the first set of data, the second set of data and the wind data, wherein the three-dimensional gas plume model identifies a source of the gas leaks.

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