公开(公告)号：US11580785B1

公开(公告)日：2023-02-14

申请号：US16436500

申请日：2019-06-10

Applicant: Amazon Technologies, Inc.

Inventor： Kaustav Kundu ,  Pahal Kamlesh Dalal ,  Nishitkumar Ashokkumar Desai ,  Jayakrishnan Kumar Eledath ,  Geoffrey A. Franz ,  Gerard Guy Medioni ,  Hoi Cheung Pang ,  Rakesh Ramakrishnan

IPC: G06T7/246 ,  G06N20/00 ,  G06V40/20 ,  G06V20/64 ,  G06V40/10

Abstract: Commercial interactions with non-discretized items such as liquids in carafes or other dispensers are detected and associated with actors using images captured by one or more digital cameras including the carafes or dispensers within their fields of view. The images are processed to detect body parts of actors and other aspects therein, and to not only determine that a commercial interaction has occurred but also identify an actor that performed the commercial interaction. Based on information or data determined from such images, movements of body parts associated with raising, lowering or rotating one or more carafes or other dispensers may be detected, and a commercial interaction involving such carafes or dispensers may be detected and associated with a specific actor accordingly.

公开(公告)号：US11922729B1

公开(公告)日：2024-03-05

申请号：US18168247

申请日：2023-02-13

Applicant: Amazon Technologies, Inc.

Inventor： Kaustav Kundu ,  Pahal Kamlesh Dalal ,  Nishitkumar Ashokkumar Desai ,  Jayakrishnan Kumar Eledath ,  Geoffrey A. Franz ,  Gerard Guy Medioni ,  Hoi Cheung Pang ,  Rakesh Ramakrishnan

IPC: G06V40/20 ,  G06N20/00 ,  G06T7/246 ,  G06V20/64 ,  G06V40/10

CPC classification number: G06V40/25 ,  G06N20/00 ,  G06T7/246 ,  G06V20/64 ,  G06V40/103 ,  G06V40/28 ,  G06T2207/30241

Abstract: Commercial interactions with non-discretized items such as liquids in carafes or other dispensers are detected and associated with actors using images captured by one or more digital cameras including the carafes or dispensers within their fields of view. The images are processed to detect body parts of actors and other aspects therein, and to not only determine that a commercial interaction has occurred but also identify an actor that performed the commercial interaction. Based on information or data determined from such images, movements of body parts associated with raising, lowering or rotating one or more carafes or other dispensers may be detected, and a commercial interaction involving such carafes or dispensers may be detected and associated with a specific actor accordingly.

公开(公告)号：US20240177049A1

公开(公告)日：2024-05-30

申请号：US18058840

申请日：2022-11-25

Applicant: Amazon Technologies, Inc.

Inventor： Lakshmi Naarayanan Ramakrishnan ,  Andrea Olgiati ,  Ankur Mehrotra ,  Karthik Gurumoorthy Subramanya Bharathy ,  Rakesh Ramakrishnan

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Confidential tuning of pre-trained machine learning models may be provided. A request associated with a model user account to fine-tune a pre-trained machine learning model with model access restrictions may be received. The pre-trained machine learning model may be one of many pre-trained machine learning models uploaded for selection and fine-tuning. The pre-trained machine learning model may be further trained using a request specified data set, with the model access restrictions and access restrictions for the data set being enforced as part of the training. Then, the fine-tuned machine learning model may be made available for invocation by an application associated with the model user account without violating the model access restrictions and data access restrictions.

公开(公告)号：US11100420B2

公开(公告)日：2021-08-24

申请号：US14460312

申请日：2014-08-14

Applicant: Amazon Technologies, Inc.

Inventor： Leo Parker Dirac ,  Jin Li ,  Rakesh Ramakrishnan ,  Tianming Zheng ,  Donghui Zhuo

IPC: G06N20/00

Abstract: A record extraction request for a data set is received at a machine learning service. A plan to perform one or more chunk-level operations (such as sampling, shuffling, splitting or partitioning for parallel computation) on chunks of the data set is generated. A set of data transfers that results in a particular chunk being stored in a particular server's memory is initiated to implement the first chunk-level operation of the sequence. A second operation such as another filtering operation or a feature processing operation is performed on a result set of the first chunk-level operation.