公开(公告)号：US20220092448A1

公开(公告)日：2022-03-24

申请号：US17383937

申请日：2021-07-23

Applicant: LUNIT INC.

Inventor： In Wan YOO ,  Donggeun YOO

IPC: G06N5/04 ,  G06N20/00

Abstract: Provided is a method for training a hint-based machine learning model configured to infer annotation information for target data, including obtaining training data for the machine learning model, wherein the training data includes a plurality of target data items provided with a plurality of annotation information items, and extracting a plurality of pixel groups from the plurality of target data items. The extracted plurality of pixel groups may be included in hint information. In addition, the method includes obtaining, from the plurality of annotation information items, a plurality of annotation classes corresponding to the extracted plurality of pixel groups to include the obtained plurality of annotation classes in the hint information, and training, by using the hint information, the machine learning model to infer the plurality of annotation information items associated with the plurality of target data items.

公开(公告)号：US20220172009A1

公开(公告)日：2022-06-02

申请号：US17671936

申请日：2022-02-15

Applicant: LUNIT INC.

Inventor： In Wan YOO

IPC: G06K9/62 ,  G06T7/11

Abstract: Provided is a method for performing a prediction work on a target image, including dividing the target image into a plurality of sub-images, generating prediction results for a plurality of pixels included in each of the plurality of divided sub-images, applying weights to the prediction results for the plurality of pixels, and merging the prediction results for the plurality of pixels applied with the weights.