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Patent Agency Ranking
公开(公告)号：US20210303877A1
公开(公告)日：2021-09-30
申请号：US16983414
申请日：2020-08-03
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
Abstract: Examples disclosed herein may involve a computing system that is configured to (i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.
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公开(公告)号：US11875680B2
公开(公告)日：2024-01-16
申请号：US16983414
申请日：2020-08-03
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
CPC classification number: G08G1/165 , G05D1/0219 , G06V10/764 , G06V10/95 , G06V20/20 , G06V20/41 , G06V20/56 , G06V20/58
Abstract: Examples disclosed herein may involve a computing system that is configured to
(i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.-
公开(公告)号：US10733463B1
公开(公告)日：2020-08-04
申请号：US16836736
申请日：2020-03-31
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
Abstract: Examples disclosed herein may involve a computing system that is configured to (i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.
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公开(公告)号：US20210191407A1
公开(公告)日：2021-06-24
申请号：US16721604
申请日：2019-12-19
Applicant: Lyft, Inc.
Inventor： Michael Jared Benisch , Ashesh Jain
Abstract: In one embodiment, a method includes, by a computing system associated with a vehicle, determining a current location of the vehicle in a first region, identifying one or more first sets of model parameters associated with the first region and one or more second sets of model parameters associated with a second region, generating, using one or more machine-learning models based on the first sets of model parameters, one or more first inferences based on first sensor data captured by the vehicle, switching the configurations of the models from the first sets of model parameters to the second sets of model parameters, generating, using the models having configurations based on the second sets of model parameters, one or more second inferences based on second sensor data generated by the sensors of the vehicle in the second region, and causing the vehicle to perform one or more operations based on the second inferences.
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公开(公告)号：US20200210887A1
公开(公告)日：2020-07-02
申请号：US16237321
申请日：2018-12-31
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Lei Zhang
Abstract: Systems, methods, and non-transitory computer-readable media can determine first sensor data captured by a first sensor of a vehicle. Second sensor data captured by a second sensor of the vehicle can be determined. Information describing the first sensor data and the second sensor data can be provided to a machine learning model trained to predict whether a pair of sensors are calibrated or mis-calibrated based on sensor data captured by the pair of sensors. A determination is made whether the first sensor and the second sensor are calibrated or mis-calibrated based on an output from the machine learning model.
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