公开(公告)号：US11960984B2

公开(公告)日：2024-04-16

申请号：US17279431

申请日：2019-09-24

Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

Inventor： Nader Salman ,  Guillaume Le Moing ,  Sepand Ossia ,  Vahagn Hakopian

IPC: G06N3/04 ,  G06N3/045 ,  G06N3/047 ,  G06N3/08 ,  G06N20/20

CPC classification number: G06N3/047 ,  G06N3/045 ,  G06N3/08 ,  G06N20/20

Abstract: An active learning framework is provided that employs a plurality of machine learning components that operate over iterations of a training phase followed by an active learning phase. In each iteration of the training phase, the machine learning components are trained from a pool of labeled observations. In the active learning phase, the machine learning components are configured to generate metrics used to control sampling of unlabeled observations for labeling such that newly labeled observations are added to a pool of labeled observations for the next iteration of the training phase. The machine learning components can include an inspection (or primary) learning component that generates a predicted label and uncertainty score for an unlabeled observation, and at least one additional component that generates a quality metric related to the unlabeled observation or the predicted label. The uncertainty score and quality metric(s) can be combined for efficient sampling of observations for labeling.

公开(公告)号：US12283197B2

公开(公告)日：2025-04-22

申请号：US17597520

申请日：2020-07-10

Applicant: Schlumberger Technology Corporation

Inventor： Nader Salman ,  Victor Amblard ,  Vahagn Hakopian

IPC: G06F17/00 ,  G06V10/774 ,  G06V10/778 ,  G06V10/82 ,  G06V20/05 ,  G09B23/40 ,  G01V1/30

Abstract: A method can include receiving labeled images; acquiring unlabeled images; performing active learning by training an inspection learner using at least a portion of the labeled images to generate a trained inspection learner that outputs information responsive to receipt of one of the unlabeled images by the trained inspection learner; based at least in part on the information, making a decision to call for labeling of the one of the unlabeled images; receiving a label for the one of the unlabeled images; and further training the inspection learner using the label.

公开(公告)号：US20220262104A1

公开(公告)日：2022-08-18

申请号：US17597520

申请日：2020-07-10

Applicant: Schlumberger Technology Corporation

Inventor： Nader Salman ,  Victor Amblard ,  Vahagn Hakopian

IPC: G06V10/778 ,  G06V10/774 ,  G06V20/05 ,  G06V10/82

Abstract: A method can include receiving labeled images; acquiring unlabeled images; performing active learning by training an inspection learner using at least a portion of the labeled images to generate a trained inspection learner that outputs information responsive to receipt of one of the unlabeled images by the trained inspection learner; based at least in part on the information, making a decision to call for labeling of the one of the unlabeled images; receiving a label for the one of the unlabeled images; and further training the inspection learner using the label.