公开(公告)号：US20140185959A1

公开(公告)日：2014-07-03

申请号：US14155434

申请日：2014-01-15

Applicant: DeepMind Technologies Limited

Inventor： Benjamin Kenneth Coppin ,  Mustafa Suleyman ,  Arun Nair

IPC: G06F17/30

CPC classification number: G06F17/30262 ,  G06K9/00 ,  G06K9/46 ,  G06K2009/4666

Abstract: A method for processing an image to generate a signature which is characteristic of a pattern within said image. The method comprising receiving an image; overlaying a window at multiple locations on said image to define a plurality of sub-images within said image, with each sub-image each having a plurality of pixels having a luminance level; determining a luminance value for each said sub-image, wherein said luminance value is derived from said luminance levels of said plurality of pixels; and combining said luminance values for each of said sub-images to form said signature. Said combining is such that said signature is independent of the location of each sub-image. A method of creating a database of images using said method of generating signatures is also described.

Abstract translation: 一种用于处理图像以生成作为所述图像内的图案的特征的签名的方法。 该方法包括接收图像; 在所述图像上的多个位置处覆盖窗口以在所述图像内定义多个子图像，每个子图像各自具有具有亮度级的多个像素; 确定每个所述子图像的亮度值，其中所述亮度值从所述多个像素的所述亮度级导出; 以及将每个所述子图像的所述亮度值组合以形成所述签名。 所述组合使得所述签名独立于每个子图像的位置。 还描述了使用所述生成签名的方法来创建图像数据库的方法。

公开(公告)号：US10885432B1

公开(公告)日：2021-01-05

申请号：US15382383

申请日：2016-12-16

Applicant: DeepMind Technologies Limited

Inventor： Gabriel Dulac-Arnold ,  Richard Andrew Evans ,  Benjamin Kenneth Coppin

IPC: G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting actions from large discrete action sets. One of the methods includes receiving a particular observation representing a particular state of an environment; and selecting an action from a discrete set of actions to be performed by an agent interacting with the environment, comprising: processing the particular observation using an actor policy network to generate an ideal point; determining, from the points that represent actions in the set, the k nearest points to the ideal point; for each nearest point of the k nearest points: processing the nearest point and the particular observation using a Q network to generate a respective Q value for the action represented by the nearest point; and selecting the action to be performed by the agent from the k actions represented by the k nearest points based on the Q values.

公开(公告)号：US08644607B1

公开(公告)日：2014-02-04

申请号：US13801027

申请日：2013-03-13

Applicant: DeepMind Technologies Limited

Inventor： Benjamin Kenneth Coppin ,  Mustafa Suleyman ,  Arun Nair

IPC: G06K9/00

CPC classification number: G06F17/30262 ,  G06K9/00 ,  G06K9/46 ,  G06K2009/4666

Abstract: A method is described for processing an image to generate a signature which is characteristic of a pattern within the image. The method includes: receiving an image; overlaying a window at multiple locations on the image to define a plurality of sub-images within the image, with each sub-image each having a plurality of pixels having a luminance level; determining a luminance value for each sub-image where the luminance value is derived from the luminance levels of the plurality of pixels; and combining the luminance values for each of the sub-images to form the signature. The combining is such that the signature is independent of the location of each sub-image. A method of creating a database of images using the method of generating signatures is also described.

Abstract translation: 描述了一种用于处理图像以生成图像中的图案的特征的签名的方法。 该方法包括：接收图像; 在图像上的多个位置处叠加窗口以在图像内定义多个子图像，每个子图像各自具有具有亮度级别的多个像素; 确定从多个像素的亮度级导出亮度值的每个子图像的亮度值; 以及组合每个子图像的亮度值以形成签名。 组合使得签名独立于每个子图像的位置。 还描述了使用生成签名的方法来创建图像数据库的方法。

公开(公告)号：US11907837B1

公开(公告)日：2024-02-20

申请号：US17131500

申请日：2020-12-22

Applicant: DeepMind Technologies Limited

Inventor： Gabriel Dulac-Arnold ,  Richard Andrew Evans ,  Benjamin Kenneth Coppin

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting actions from large discrete action sets. One of the methods includes receiving a particular observation representing a particular state of an environment; and selecting an action from a discrete set of actions to be performed by an agent interacting with the environment, comprising: processing the particular observation using an actor policy network to generate an ideal point; determining, from the points that represent actions in the set, the k nearest points to the ideal point; for each nearest point of the k nearest points: processing the nearest point and the particular observation using a Q network to generate a respective Q value for the action represented by the nearest point; and selecting the action to be performed by the agent from the k actions represented by the k nearest points based on the Q values.