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    CAMERA BASED TRAFFIC MANAGEMENT FOR A TRAFFIC CIRCLE
    1.
    发明公开
    CAMERA BASED TRAFFIC MANAGEMENT FOR A TRAFFIC CIRCLE 审中-公开

    公开(公告)号：US20240362919A1

    公开(公告)日：2024-10-31

    申请号：US18307377

    申请日：2023-04-26

    申请人： Evelyn Shen ,  Crystal Jing Li

    发明人： Evelyn Shen ,  Crystal Jing Li

    IPC分类号： G06V20/54 ,  G06T7/246 ,  G06V20/62

    CPC分类号： G06V20/54 ,  G06T7/246 ,  G06V20/625 ,  G06T2207/10016 ,  G06T2207/20221 ,  G06T2207/30196 ,  G06T2207/30236

    摘要： Traffic circles are equipped with one or more cameras at its entrances of the traffic circles. The cameras, connected with sensors and central control units, determine speed and moving directions of vehicles entering or circling inside the traffic circle, based on artificial intelligence and machine learning. The speed of a vehicles can be determined by tracking a distance of the car to the camera and a distance between the camera lens and an image sensor inside the camera. The moving direction of the car can be determined by tracking the moving pattern of the car inside the traffic circle, among other ways. The central control determines the traffic pattern inside the traffic circle, gives signals like flashing lights, to vehicles entering the traffic circle to stop and yield to emergency vehicles, pedestrian crossing, or other vehicles approaching the entrance if the incoming vehicles do not have clearances to enter.

    MULTI-SPECTRUM CAMERA SYSTEM TO ENHANCE FOOD REGONITION
    2.
    发明公开
    MULTI-SPECTRUM CAMERA SYSTEM TO ENHANCE FOOD REGONITION 审中-公开

    公开(公告)号：US20240096117A1

    公开(公告)日：2024-03-21

    申请号：US17933848

    申请日：2022-09-20

    申请人： Crystal Jing Li ,  Evelyn Shen ,  Nash Young

    发明人： Crystal Jing Li ,  Evelyn Shen ,  Nash Young

    IPC分类号： G06V20/68 ,  G06V10/143

    CPC分类号： G06V20/68 ,  G06V10/143

    摘要： The described embodiments relate generally to a camera system to enhance food and material identification. More particularly, the described embodiments relate to using a plurality of camera sensors and LED light sources, including visible image sensors, visible light source, near infrared (NIR) image sensors, two or more bands of infrared light sources, depth camera images, and synchronized light source. The visible image data, NIR image data, depth image data are processed to obtain combined image data. A machine learning algorithm is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item.