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UiPath Face Recognition Framework

UiPath Face Recognition Framework

by Internal Labs

7

Solution

Downloads

647

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Summary

Summary

The recognition is completely based on deep learning neural network and implanted using Tensorflow framework

Overview

Overview

In UiPath Attended Robot Framework you can find a TensorFlow implementation of the face recognizer described in the paper FaceNet: A Unified Embedding for Face Recognition and Clustering. The project also uses ideas from the paper Deep Face Recognition from the Visual Geometry Group at Oxford.

The framework allows you to add an extra layer of security in attended scenarios. In order to do that the robot will ask your name and to take few photos. 

The model needs to be trained once, for each user that is allowed to kick start the digital assistent for sensitive processes. 

Face Recognition Framework is splited in two major segments:

  1. Training: When the robot gets train with new photos for an existing user or a new one.
  2. Execution of a business process by having in front of the computer a known user.

Features

Features

Extra layer of security. Biometric recognition

Additional Information

Additional Information

Dependencies

Must have: Python 3.6 with pip 10.0.1 Tensorflow (1.4.0) Scipy (0.17.0) Scikit-learn (0.19.1) Opencv (2.4.9.1)

Code Language

Visual Basic

Publisher

Internal Labs

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License & Privacy

License Agreement

Privacy Terms

Technical

Version

1.0.1

Updated

Feb 26, 2020

Works with

Studio: 20.4 - 22.10

Certification

Silver Certified

Support

UiPath Community Support

Resources

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