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公开(公告)号：US11741736B2
公开(公告)日：2023-08-29
申请号：US17556451
申请日：2021-12-20
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
IPC分类号： G06V40/10 , G06N3/08 , G06T7/246 , G06V10/26 , G06V20/52 , G06N3/045 , G06V10/82 , G06V10/44
CPC分类号： G06V40/103 , G06N3/045 , G06N3/08 , G06T7/248 , G06V10/26 , G06V10/454 , G06V10/82 , G06V20/52 , G06V40/10 , G06T2207/10016 , G06T2207/20084 , G06T2207/30196 , G06T2207/30232 , G06T2207/30241
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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公开(公告)号：US12087077B2
公开(公告)日：2024-09-10
申请号：US18347471
申请日：2023-07-05
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
IPC分类号： G06V40/10 , G06N3/045 , G06N3/08 , G06T7/246 , G06V10/26 , G06V10/44 , G06V10/82 , G06V20/52
CPC分类号： G06V40/103 , G06N3/045 , G06N3/08 , G06T7/248 , G06V10/26 , G06V10/454 , G06V10/82 , G06V20/52 , G06V40/10 , G06T2207/10016 , G06T2207/20084 , G06T2207/30196 , G06T2207/30232 , G06T2207/30241
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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公开(公告)号：US20230351795A1
公开(公告)日：2023-11-02
申请号：US18347471
申请日：2023-07-05
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
IPC分类号： G06V40/10 , G06N3/08 , G06T7/246 , G06V10/26 , G06V20/52 , G06N3/045 , G06V10/82 , G06V10/44
CPC分类号： G06V40/103 , G06N3/08 , G06T7/248 , G06V10/26 , G06V20/52 , G06V40/10 , G06N3/045 , G06V10/82 , G06V10/454 , G06T2207/30232 , G06T2207/10016 , G06T2207/20084 , G06T2207/30196 , G06T2207/30241
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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公开(公告)号：US11205086B2
公开(公告)日：2021-12-21
申请号：US16678100
申请日：2019-11-08
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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公开(公告)号：US20220114800A1
公开(公告)日：2022-04-14
申请号：US17556451
申请日：2021-12-20
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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公开(公告)号：US20200151489A1
公开(公告)日：2020-05-14
申请号：US16678100
申请日：2019-11-08
申请人： NVIDIA Corporation
发明人： Parthasarathy Sriram , Fnu Ratnesh Kumar , Anil Ubale , Farzin Aghdasi , Yan Zhai , Subhashree Radhakrishnan
摘要： In various examples, sensor data—such as masked sensor data—may be used as input to a machine learning model to determine a confidence for object to person associations. The masked sensor data may focus the machine learning model on particular regions of the image that correspond to persons, objects, or some combination thereof. In some embodiments, coordinates corresponding to persons, objects, or combinations thereof, in addition to area ratios between various regions of the image corresponding to the persons, objects, or combinations thereof, may be used to further aid the machine learning model in focusing on important regions of the image for determining the object to person associations.
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