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Facial recognition framework using deep learning for attended robots

A technology of deep learning and robotics, applied to computer components, character and pattern recognition, instruments, etc., can solve problems such as high risk of data destruction

Pending Publication Date: 2022-01-11
UIPATH INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The risk of data breaches can be particularly high in digital environments where manned robots handle confidential data

Method used

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  • Facial recognition framework using deep learning for attended robots
  • Facial recognition framework using deep learning for attended robots
  • Facial recognition framework using deep learning for attended robots

Examples

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Embodiment Construction

[0016] For the methods and processes described herein, the recited steps may be performed out of order, in any order, and sub-steps not explicitly described or shown may be performed. Additionally, "coupled" or "operably coupled" may mean that objects are linked, but there may be zero or more intermediate objects between the linked objects. Furthermore, any combination of the disclosed features / elements can be used in one or more embodiments. When it comes to using "A or B", it can include A, B, or A and B, which can similarly be extended to longer lists. When the notation X / Y is used, it can include either X or Y. Alternatively, when the notation X / Y is used, it may include both X and Y. X / Y notation can similarly be extended to longer lists with the same interpretation logic.

[0017] Figure 1A is an illustration of Robotic Process Automation (RPA) development, design, operation or execution 100 . Designer 102, sometimes referred to as a studio, development platform, d...

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PUM

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Abstract

A facial recognition framework may be configured for robotic process automation (RPA) to automate a workflow for an application interface. A set of images of a user may be captured after the robot is initiated for the automated workflow. The set of images may be utilized by a deep learning neural network model to identify facial characteristics. The automated workflow may be performed by an attended robot based on successful validation of the user with the facial characteristics and credentials of the user for the attended robot.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of U.S. Application No. 16 / 595,694, filed October 8, 2019, the contents of which are incorporated herein by reference. Background technique [0003] Robotic Process Automation (RPA) can automate repetitive operations, functions or workflows in enterprise platforms, virtual machine (VM) provisioning, remote desktops, cloud computing, desktop applications, mobile applications, and more. Similar to other digital environments, data or security breaches in RPA can occur due to weaknesses such as employee negligence, accidental leaks, inattention, viruses, etc. In digital environments where manned robots handle confidential data, the risk of data breaches can be particularly high. [0004] Security and authentication procedures can be configured to prevent data corruption. Authentication based on facial or other biometric recognition can be used for RPA based on attended bots to allow cer...

Claims

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Application Information

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IPC IPC(8): G06F9/455G06F21/32G06K9/00G06K9/62G06V10/764
CPCG06F9/45512G06F21/32G06F18/2414G06V40/172G06V10/82G06V10/764G05B19/042G05B2219/24162G06V40/166
Inventor R-A·伊奥丹科D-A·默里
Owner UIPATH INC