OBJECT DISCRIMINATION DEVICE
    33.
    发明公开

    公开(公告)号:US20240290066A1

    公开(公告)日:2024-08-29

    申请号:US18569697

    申请日:2021-06-17

    申请人: NEC Corporation

    发明人: Takuya OGAWA

    摘要: An object discrimination device includes an acquisition unit, a binarization unit, a feature extraction unit, and an area computation unit. The acquisition unit acquires an image of an imaging area where objects are aligned in an array from a direction orthogonal to the object alignment direction. The binarization unit generates, from the image, a binarized image of an object area that is an area where the object is present. The feature extraction unit computes a total pixel value for each array of pixel values aligned in a direction orthogonal to the object alignment direction in the binarized image, and generates a total pixel value array in which the total pixel values for the respective arrays are aligned in the object alignment direction. The area computation unit computes an object boundary in the alignment direction of the objects in the binarized image on the basis of the total pixel value array.

    Method and system for training a neural network

    公开(公告)号:US11983241B2

    公开(公告)日:2024-05-14

    申请号:US17189035

    申请日:2021-03-01

    摘要: A method for training a neural network for detecting a plurality of classes of object within a sample comprises providing a training data set comprising a plurality of samples, each annotated according to whether the samples include labelled objects of interest. In a first type of samples, all objects of interest are labelled according to their class and comprise a foreground of the samples, the remainder of the samples comprising background. In a second type of samples, some objects of interest are labelled in a foreground and their background may comprise unlabelled objects. A third type of samples comprise only background comprising no objects of interest. Negative mining is only performed on the results of processing the first and third types of samples.