UNDER-DISPLAY CAMERA SYSTEMS AND METHODS
    19.
    发明公开

    公开(公告)号:US20230164426A1

    公开(公告)日:2023-05-25

    申请号:US17768092

    申请日:2020-10-16

    摘要: An example image capture device includes a display configured to display captured images, a camera sensor, the camera sensor being disposed to receive light through at least a portion of the display, memory configured to store captured images, and one or more processors coupled to the camera sensor, the display, and the memory. The one or more processors are configured to receive a signal from a sensor. The one or more processors are configured to determine, based at least in part on the signal, a user interface mode. The user interface mode includes a first mode having a first number of black pixels or a second mode having a second number of black pixels. The first number is greater than the second number. The one or more processors are also configured to receive image data from the camera sensor.

    Automated Image Acquisition System for Automated Training of Artificial Intelligence Algorithms to Recognize Objects and Their Position and Orientation

    公开(公告)号:US20230143670A1

    公开(公告)日:2023-05-11

    申请号:US17916283

    申请日:2021-03-28

    申请人: Cognivix s.r.l.

    摘要: The present invention represents an automated system for training a machine learning algorithm for recognizing the position and orientation of objects. Given one or more objects and the corresponding three-dimensional mathematical model(s), the proposed system acquires, in an automated manner, images of the one or more objects under examination and generates, again in an automated manner, the parameters of a machine learning algorithm for recognising the objects for which training has been done. The system proposed in the present innovation comprises at least one optical image acquisition system, at least one mechanical system for moving the optical image acquisition system, or the object under examination, or both, to arbitrary positions in three-dimensional space, at least one screen (or other system) capable of generating arbitrary images, at least one electronic system, and at least one software system for controlling the optical image acquisition system, the mechanical positioning system, and for computing the weights of the neural network used for automatic recognition of the object for which the training has been done.