公开(公告)号：US10824916B2

公开(公告)日：2020-11-03

申请号：US16126748

申请日：2018-09-10

Applicant: SRI International

Inventor： Karan Sikka ,  Ajay Divakaran ,  Parneet Kaur

IPC: G06N3/08 ,  G06K9/62

Abstract: Systems and methods for improving the accuracy of a computer system for object identification/classification through the use of weakly supervised learning are provided herein. In some embodiments, the method includes (a) receiving at least one set of curated data, wherein the curated data includes labeled images, (b) using the curated data to train a deep network model for identifying objects within images, wherein the trained deep network model has a first accuracy level for identifying objects, receiving a first target accuracy level for object identification of the deep network model, determining, automatically via the computer system, an amount of weakly labeled data needed to train the deep network model to achieve the first target accuracy level, and augmenting the deep network model using weakly supervised learning and the weakly labeled data to achieve the first target accuracy level for object identification by the deep network model.

公开(公告)号：US20200082224A1

公开(公告)日：2020-03-12

申请号：US16126748

申请日：2018-09-10

Applicant: SRI International

Inventor： Karan Sikka ,  Ajay Divakaran ,  Parneet Kaur

IPC: G06K9/62 ,  G06N3/08

Abstract: Systems and methods for improving the accuracy of a computer system for object identification/classification through the use of weakly supervised learning are provided herein. In some embodiments, the method includes (a) receiving at least one set of curated data, wherein the curated data includes labeled images, (b) using the curated data to train a deep network model for identifying objects within images, wherein the trained deep network model has a first accuracy level for identifying objects, receiving a first target accuracy level for object identification of the deep network model, determining, automatically via the computer system, an amount of weakly labeled data needed to train the deep network model to achieve the first target accuracy level, and augmenting the deep network model using weakly supervised learning and the weakly labeled data to achieve the first target accuracy level for object identification by the deep network model.