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UiPath Face Recognition Framework

Machine Learning Model

Machine Learning Model

Updated: October 27th, 2020

Published: March 25th, 2019

Downloads: 511

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UiPath Face Recognition Framework

Machine Learning Model

Summary: 

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

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.

Details

Benefits

Extra layer of security. Biometric recognition

Compatibility

Any Windows machine with Python 3.6, pip 10.0.1. and the packages from Prerequisites/requirements.txt

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)

Resources

- Installation_Guide.pdf

Licensing

By clicking download you agree to the following license.