公开(公告)号：US20220083861A1

公开(公告)日：2022-03-17

申请号：US17532323

申请日：2021-11-22

Applicant: Samsung Electronics Co., Ltd.

Inventor： Xianzhi DU ,  Mostafa EL-KHAMY ,  Jungwon LEE

IPC: G06N3/08 ,  G06N20/00 ,  G06K9/62 ,  G06N3/04 ,  G06N7/00

Abstract: Methods and apparatuses for deep learning training are provided which include receiving a candidate unit for classification. The candidate unit including an intersection area between a ground-truth bounding box and a detection box. The candidate unit is classified by assigning a label that is a probability value that a given feature is observed in the intersection area. Deep learning training is performed using the assigned label of the classified candidate unit.

公开(公告)号：US20180181881A1

公开(公告)日：2018-06-28

申请号：US15588223

申请日：2017-05-05

Applicant: Samsung Electronics Co., Ltd.

Inventor： Xianzhi DU ,  Mostafa EL-KHAMY ,  Jungwon LEE

IPC: G06N99/00 ,  G06K9/62 ,  G06N5/04 ,  G06N3/08

CPC classification number: G06N20/00 ,  G06K9/62 ,  G06K9/6256 ,  G06N3/0454 ,  G06N3/084 ,  G06N7/005

Abstract: Apparatuses and methods of manufacturing same, systems, and methods for training deep learning machines are described. In one aspect, candidate units, such as detection bounding boxes in images or phones of an input audio feature, are classified using soft labelling, where at least label has a range of possible values between 0 and 1 based, in the case of images, on the overlap of a detection bounding box and one or more ground-truth bounding boxes for one or more classes.