公开(公告)号：US11867801B2

公开(公告)日：2024-01-09

申请号：US17354557

申请日：2021-06-22

Applicant: Beijing Baidu Netcom Science and Technology Co., LTD

Inventor： Xiaoqing Ye ,  Xiao Tan ,  Hao Sun

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/68 ,  G01S13/931 ,  G06T7/521 ,  G01S13/42 ,  G01S13/86 ,  G06N3/08 ,  G06T7/60 ,  G06V20/52 ,  G06V30/24 ,  G06F18/214 ,  G06F18/25 ,  G06F18/21 ,  G06V10/25 ,  G06V10/80 ,  G06V10/44 ,  G06V10/98 ,  G06V20/54 ,  G06V20/64

CPC classification number: G01S13/931 ,  G01S13/42 ,  G01S13/867 ,  G06F18/214 ,  G06F18/217 ,  G06F18/25 ,  G06N3/08 ,  G06T7/521 ,  G06T7/60 ,  G06V10/25 ,  G06V10/454 ,  G06V10/80 ,  G06V10/98 ,  G06V20/52 ,  G06V20/54 ,  G06V20/64 ,  G06V30/248 ,  G06T2207/10028 ,  G06T2207/30236 ,  G06V30/2552 ,  G06V2201/00 ,  G06V2201/08

Abstract: A vehicle information detection method, a method for training a detection model, an electronic device and a storage medium are provided, and relates to the technical field of artificial intelligence, in particular to the technical field of computer vision and deep learning. The method includes: performing a first target detection operation based on an image of a target vehicle, to obtain a first detection result for target information of the target vehicle; performing an error detection operation based on the first detection result, to obtain error information; and performing a second target detection operation based on the first detection result and the error information, to obtain a second detection result for the target information.

公开(公告)号：US11854305B2

公开(公告)日：2023-12-26

申请号：US17315319

申请日：2021-05-09

Applicant: International Business Machines Corporation

Inventor： Bo Wu ,  Chuang Gan ,  Dakuo Wang ,  Kaizhi Qian

IPC: G06V40/20 ,  G06T7/246 ,  G06F3/01 ,  G06V20/40 ,  G06F18/2133

CPC classification number: G06V40/23 ,  G06F3/011 ,  G06F18/2133 ,  G06T7/246 ,  G06V20/46 ,  G06T2207/10016 ,  G06T2207/20076 ,  G06T2207/20084 ,  G06T2207/30196 ,  G06V2201/00

Abstract: A bi-directional spatial-temporal transformer neural network (BDSTT) is trained to predict original coordinates of a skeletal joint in a specific frame through relative relationships of the skeletal joint to other joints and to the state of the skeletal joint in other frames. Obtain a plurality of frames comprising coordinates of the skeletal joint and coordinates of other joints. Produce a spatially masked frame by masking the original coordinates of the skeletal joint. Provide the specific frame, the spatially masked frame, and at least one more frame to a coordinate prediction head of the BDSTT. Obtain, from the coordinate prediction head, a prediction of coordinates for the skeletal joint. Adjust parameters of the BDSTT until a mean-squared error, between the prediction of coordinates for the skeletal joint and the original coordinates of the skeletal joint, converges.

公开(公告)号：US12062240B2

公开(公告)日：2024-08-13

申请号：US17477661

申请日：2021-09-17

Applicant: VergeIQ, LLC

Inventor： Ricky Samona ,  Christopher Benham

IPC: G06V20/56 ,  B62J45/416 ,  B62J45/422 ,  B62M6/80 ,  G06N20/00 ,  G06V20/13

CPC classification number: G06V20/56 ,  B62J45/416 ,  B62J45/422 ,  B62M6/80 ,  G06N20/00 ,  G06V20/13 ,  G06V2201/00

Abstract: A monitoring system can include an electronic device operably coupled with a vehicle. One or more sensors operably can be operably coupled with the electronic device. A user interface can be operably coupled with the electronic device. A controller can be operably coupled with the electronic device. The controller can be configured to receive data from the one or more sensors and provide an instruction to the electronic device based on the data from the one or more sensors, wherein the instruction is related to mitigating an upcoming information of interest along a route.