公开(公告)号：US12147878B2

公开(公告)日：2024-11-19

申请号：US17106026

申请日：2020-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Barath Balasubramanian ,  Rahul Bhotika ,  Niels Brouwers ,  Ranju Das ,  Prakash Krishnan ,  Shaun Ryan James McDowell ,  Anushri Mainthia ,  Rakesh Madhavan Nambiar ,  Anant Patel ,  Avinash Aghoram Ravichandran ,  Joaquin Zepeda Salvatierra ,  Gurumurthy Swaminathan

IPC: G06N3/091 ,  G06F16/23 ,  G06F18/21 ,  G06F18/214 ,  G06N3/088 ,  G06N5/04 ,  G06N20/00 ,  G06T7/00

Abstract: Techniques for feedback-based training may include selecting a scoring machine learning model based at least in part on a test metric, and applying the model on an unlabeled dataset to generate, per dataset item of the unlabeled dataset, a prediction and an importance ranking score for the prediction. Techniques for feedback-based training may further include selecting, based on the importance ranking scores, a result of the application of the model on the unlabeled dataset, providing the result and requesting feedback on the result via a graphical user interface, receiving the feedback via the graphical user interface, adding data from the unlabeled dataset into a training dataset when the feedback indicates a verified result, and retraining the model using the training dataset with the data added from the unlabeled dataset to generate a retrained model.

公开(公告)号：US11983243B2

公开(公告)日：2024-05-14

申请号：US17106023

申请日：2020-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Barath Balasubramanian ,  Rahul Bhotika ,  Niels Brouwers ,  Ranju Das ,  Prakash Krishnan ,  Shaun Ryan James Mcdowell ,  Anushri Mainthia ,  Rakesh Madhavan Nambiar ,  Anant Patel ,  Avinash Aghoram Ravichandran ,  Joaquin Zepeda Salvatierra ,  Gurumurthy Swaminathan

IPC: G06N20/00 ,  G06F9/451 ,  G06F18/21 ,  G06F18/214 ,  G06N3/088 ,  G06N3/09 ,  G06V10/70 ,  G06V10/774 ,  G06V10/778 ,  H04L9/40

CPC classification number: G06F18/2148 ,  G06F9/451 ,  G06F18/2155 ,  G06F18/2178 ,  G06N3/088 ,  G06N3/09 ,  G06N20/00 ,  G06V10/70 ,  G06V10/7753 ,  G06V10/7784 ,  H04L63/1425 ,  G06T2207/20081

Abstract: Techniques for anomaly detection are described. An exemplary method includes receiving one or more requests to train an anomaly detection machine learning model using feedback-based training, the request to indicate one or more of a type of analysis to perform, a model selection indication, and a configuration for a training dataset; training the anomaly detection machine learning model according to the one or more requests using the training data; performing feedback-based training on the trained anomaly detection machine learning model; and using the retrained anomaly detection machine learning model.

公开(公告)号：US11741592B2

公开(公告)日：2023-08-29

申请号：US17106028

申请日：2020-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Joaquin Zepeda Salvatierra ,  Anant Patel ,  Shaun Ryan James McDowell ,  Prakash Krishnan ,  Ranju Das ,  Niels Brouwers ,  Barath Balasubramanian

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/174

CPC classification number: G06T7/0004 ,  G06T7/11 ,  G06T7/174 ,  G06T2207/20081 ,  G06T2207/20092 ,  G06T2207/30164

Abstract: Techniques for anomaly detection are described. An exemplary method includes receiving a request to create a training data set from at least one image, the request to include an indication of the at least one image and at least one indication of an operation to perform on the at least one image to generate a plurality of images from the at least one image; creating a training dataset by extracting one or more chunks from a first at least one image according to the request; and receiving one or more requests to train an anomaly detection machine learning model using the created training dataset; and training an anomaly detection machine learning model according to one or more requests using the created training data.