Machine learning based privacy mechanisms

The objective of this project is to learn latent representations using a Machine Learning approach for image sanitization in Smart Homes surveillance cameras. Three Autoencoder Machine Learning models are explored in this project 1) Adversarial Autoencoder 2) Variational Autoencoder 3) Variational F...

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Main Author: Lim, Royce Jin Feng
Other Authors: Tay, Wee Peng
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/140365
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1403652023-07-07T18:43:05Z Machine learning based privacy mechanisms Lim, Royce Jin Feng Tay, Wee Peng School of Electrical and Electronic Engineering wptay@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems The objective of this project is to learn latent representations using a Machine Learning approach for image sanitization in Smart Homes surveillance cameras. Three Autoencoder Machine Learning models are explored in this project 1) Adversarial Autoencoder 2) Variational Autoencoder 3) Variational Fair Autoencoder. These autoencoders are able to learn latent representations of the input data, which can be processed to encourage separation between the input data and private information which are classified in the model as sensitive variables. This provides the capability of sanitizing the image of the Smart Home user’s private information. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-28T05:39:48Z 2020-05-28T05:39:48Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140365 en A3250-191 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Lim, Royce Jin Feng
Machine learning based privacy mechanisms
description The objective of this project is to learn latent representations using a Machine Learning approach for image sanitization in Smart Homes surveillance cameras. Three Autoencoder Machine Learning models are explored in this project 1) Adversarial Autoencoder 2) Variational Autoencoder 3) Variational Fair Autoencoder. These autoencoders are able to learn latent representations of the input data, which can be processed to encourage separation between the input data and private information which are classified in the model as sensitive variables. This provides the capability of sanitizing the image of the Smart Home user’s private information.
author2 Tay, Wee Peng
author_facet Tay, Wee Peng
Lim, Royce Jin Feng
format Final Year Project
author Lim, Royce Jin Feng
author_sort Lim, Royce Jin Feng
title Machine learning based privacy mechanisms
title_short Machine learning based privacy mechanisms
title_full Machine learning based privacy mechanisms
title_fullStr Machine learning based privacy mechanisms
title_full_unstemmed Machine learning based privacy mechanisms
title_sort machine learning based privacy mechanisms
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/140365
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