公开(公告)号：US20240312197A1

公开(公告)日：2024-09-19

申请号：US18605594

申请日：2024-03-14

Applicant: SRI International

Inventor： Han-Pang Chiu ,  Niluthpol C. Mithun ,  Supun Samarasekera ,  Abhinav Rajvanshi ,  Xingchen Zhao ,  Md Nazmul Karim

IPC: G06V10/82 ,  G06V10/771 ,  G06V10/774 ,  G06V10/776

CPC classification number: G06V10/82 ,  G06V10/771 ,  G06V10/7753 ,  G06V10/776

Abstract: In general, techniques are described for unsupervised domain adaptation of models with pseudo-label curation. In an example, a method includes generating a plurality of pseudo-labels for a dataset of unlabeled data using a source machine learning model; estimating a reliability of each pseudo-label of the plurality of pseudo-labels using one or more reliability measures; selecting a subset of the plurality of pseudo-labels having estimated reliabilities that satisfy a reliability threshold; and training, using one or more curriculum learning techniques, a target machine learning model starting with the selected subset of the plurality of pseudo-labels and the corresponding unlabeled data.