公开(公告)号：US11768914B1

公开(公告)日：2023-09-26

申请号：US17711391

申请日：2022-04-01

Applicant: Amazon Technologies, Inc.

Inventor： Vinayak Ashutosh Agarwal ,  Jason Lenox Copeland ,  Matthew James Wood ,  Long Gao ,  Ricardo Elizondo Costa ,  Jiajun Sun ,  Naga Krishna Teja Komma

IPC: G06N20/00 ,  G06F18/214 ,  G06V10/94 ,  G06F18/21 ,  G06F18/2413

CPC classification number: G06F18/214 ,  G06F18/217 ,  G06F18/2413 ,  G06N20/00 ,  G06V10/95

Abstract: Techniques for training a machine learning model based on captured images are described. A method described include filtering a first set of collected images using one or more machine learning models; labeling the first set of filtered, collected images using a data labeling service using a service of the provider network; training a machine learning model from a machine learning algorithm using the first set of filtered, collected images using a service of the provider network; and causing deployment of the trained machine learning model onto a device.

公开(公告)号：US11295165B1

公开(公告)日：2022-04-05

申请号：US16587400

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Vinayak Ashutosh Agarwal ,  Jason Lenox Copeland ,  Matthew James Wood ,  Long Gao ,  Ricardo Elizondo Costa ,  Jiajun Sun ,  Naga Krishna Teja Komma

IPC: G06N20/00 ,  G06K9/62 ,  G06K9/00

Abstract: Techniques for training a machine learning model based on captured images are described. A method described include filtering a first set of collected images using one or more machine learning models; labeling the first set of filtered, collected images using a data labeling service using a service of the provider network; training a machine learning model from a machine learning algorithm using the first set of filtered, collected images using a service of the provider network; and causing deployment of the trained machine learning model onto a device.

公开(公告)号：US11488310B1

公开(公告)日：2022-11-01

申请号：US16587398

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Aravind Nagarajan ,  Jason Lenox Copeland ,  Vinayak Ashutosh Agarwal ,  Alexei Shlychkov

IPC: G06T7/11 ,  G06N20/00 ,  G06K9/00 ,  G06V20/10

Abstract: Techniques for applying one or more machine learning models to a sub-region less than all of an image scene are described. An example is receiving first sub-region from an image; analyzing the received first sub-region of the image using the indicated least one machine learning model to perform the analyzing of the first sub-region of the scene; and outputting a result of the analyzing.

公开(公告)号：US11275631B1

公开(公告)日：2022-03-15

申请号：US16587395

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Alexei Shlychkov ,  Vinayak Ashutosh Agarwal ,  Jason Lenox Copeland

IPC: G06F9/54 ,  G06F12/02 ,  G06F9/50 ,  G06F5/10 ,  G06F9/52

Abstract: Techniques for implementing an on-demand serverless compute system that uses shared memory to share data between on-demand serverless compute applications are described. In some examples, a daemon of an edge device providing on-demand serverless compute is to: register launched one or more launched on-demand serverless applications, read a deployment configuration for an application using the one or more launched on-demand serverless applications, per the read deployment configuration, launch at least one data source and at least one data sink, per launched data source, register the launched data source with the device daemon, per launched data sink, register the launched data sink thread with the device daemon, match registered, launched data sources with registered, launched data sinks and launched on-demand serverless applications as defined in the deployment configuration, and for each match, register a connection first in, first out structure to be used to share data on an event driven basis between launched on-demand serverless applications.