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...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/140365 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-140365 |
---|---|
record_format |
dspace |
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 |
_version_ |
1772825803335139328 |