公开(公告)号：US11836909B2

公开(公告)日：2023-12-05

申请号：US17584914

申请日：2022-01-26

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  David Greenlaw ,  Tony Altinis

IPC: G06T7/00 ,  G06V10/774 ,  G06V10/762 ,  G06T7/10

CPC classification number: G06T7/0004 ,  G06T7/10 ,  G06V10/762 ,  G06V10/7747 ,  G06T2207/20081 ,  G06T2207/20092

Abstract: A computing entity is described that obtains at least one inspection image of an at least partially fabricated product and causes the at least one inspection image to be processed by a product inspection engine. The product inspection engine includes a machine learning-trained model. The computing entity obtains an inspection result determined based on the processing of the at least one inspection image by the product inspection engine; identifies one or more training images stored in an image database based at least in part on the at least one inspection image; associates automatically generated labeling data with the one or more training images based at least in part on the inspection result determined by the processing of the at least one inspection image; and causes training of the product inspection engine using the one or more training images and the associated labeling data.

公开(公告)号：US20230237635A1

公开(公告)日：2023-07-27

申请号：US17584914

申请日：2022-01-26

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  David Greenlaw ,  Tony Altinis

IPC: G06T7/00 ,  G06V10/774 ,  G06T7/10 ,  G06V10/762

CPC classification number: G06T7/0004 ,  G06V10/7747 ,  G06T7/10 ,  G06V10/762 ,  G06T2207/20081 ,  G06T2207/20092

Abstract: A computing entity is described that obtains at least one inspection image of an at least partially fabricated product and causes the at least one inspection image to be processed by a product inspection engine. The product inspection engine includes a machine learning-trained model. The computing entity obtains an inspection result determined based on the processing of the at least one inspection image by the product inspection engine; identifies one or more training images stored in an image database based at least in part on the at least one inspection image; associates automatically generated labeling data with the one or more training images based at least in part on the inspection result determined by the processing of the at least one inspection image; and causes training of the product inspection engine using the one or more training images and the associated labeling data.