Predicting and correcting vegetation state

    公开(公告)号:GB2602929A

    公开(公告)日:2022-07-20

    申请号:GB202205196

    申请日:2020-09-24

    Applicant: IBM

    Abstract: Methods and systems for managing vegetation include training a machine learning model based on an image of a training data region before a weather event, an image of the training data region after the weather event, and information regarding the weather event. A risk score is generated for a second region using the trained machine learning model based on an image of the second region and predicted weather information for the second region. The risk score is determined to indicate high-risk vegetation in the second region. A corrective action is performed to reduce the risk of vegetation in the second region.

    Carrier-resolved photo-hall system and method

    公开(公告)号:GB2596770A

    公开(公告)日:2022-01-05

    申请号:GB202115227

    申请日:2020-03-17

    Applicant: IBM

    Abstract: Systems and methods are provided that facilitate high-sensitivity, carrier-resolved photo-Hall effect measurements. Majority and minority carrier properties can be measured and determined simultaneously. In one aspect, a system(200) and method determine majority carrier type, density and mobility and, with modulated illumination, minority carrier mobility and photocarrier density. In another aspect, a system(200) and method can determine hole and electron mobility, photocarrier density, absorbed photon density, recombination lifetime and diffusion length forhole, electron and ambipolar transport.

    System and method of incremental learning for object detection

    公开(公告)号:GB2596448A

    公开(公告)日:2021-12-29

    申请号:GB202113217

    申请日:2020-03-13

    Applicant: IBM

    Abstract: Methods and systems perform incremental learning object detection in images and/or videos without catastrophic forgetting of previously-learned object classes. A two-stage neural network object detector is trained to locate and identify objects pertaining to an additional object class by iteratively updating the two-stage neural network object detector until an overall detection accuracy criterion is met. The updating is performed so as to balance minimizing a loss of an initial ability to locate and identify objects pertaining to the previously-learned object classes and maximizing an ability to additionally locate and identify the objects pertaining to the additional object class. Assessing whether the overall detection accuracy criterion is met compares outputs of an initial version of the two- stage neural network object detector with a current region proposal output by a current version of the two-stage neural network object detector to determining a region proposal distillation loss and a previously-learned-object identification distillation loss.

    Carrier-resolved photo-hall system and method

    公开(公告)号:GB2596770B

    公开(公告)日:2022-05-25

    申请号:GB202115227

    申请日:2020-03-17

    Applicant: IBM

    Abstract: Systems and methods are provided that facilitate high-sensitivity, carrier-resolved photo-Hall effect measurements. Majority and minority carrier properties can be measured and determined simultaneously. In one aspect, a system and method determine majority carrier type, density and mobility and, with modulated illumination, minority carrier mobility and photocarrier density. In another aspect, a system and method can determine hole and electron mobility, photocarrier density, absorbed photon density, recombination lifetime and diffusion length for hole, electron and ambipolar transport.

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