IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI

<b>ABSTRACT:</b><br> <br /> Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. This thesis learn how to have the solution of face identification and face authentification with neural ne...

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Main Author: Mulyani, Yessy
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/3105
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:3105
spelling id-itb.:31052005-12-05T08:05:08ZIDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI Mulyani, Yessy Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/3105 <b>ABSTRACT:</b><br> <br /> Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. This thesis learn how to have the solution of face identification and face authentification with neural network approach. The Self Organizing Map neural network and the Convolutional Neural network use in this solution.</p> The Self Organizing Map provides a quantization of the images samples into a topological space where inputs that are nearby in the original space are also nearby in the outputs space, thereby providing dimensionality reduction and invariance to minor changes in the sample images, and the convolutional neural network provides for partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers with the backpropagation algorithm. For best parameter, this system can do face identification and authentification in 76% and 75% measure of confidence respectively. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <b>ABSTRACT:</b><br> <br /> Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. This thesis learn how to have the solution of face identification and face authentification with neural network approach. The Self Organizing Map neural network and the Convolutional Neural network use in this solution.</p> The Self Organizing Map provides a quantization of the images samples into a topological space where inputs that are nearby in the original space are also nearby in the outputs space, thereby providing dimensionality reduction and invariance to minor changes in the sample images, and the convolutional neural network provides for partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers with the backpropagation algorithm. For best parameter, this system can do face identification and authentification in 76% and 75% measure of confidence respectively.
format Theses
author Mulyani, Yessy
spellingShingle Mulyani, Yessy
IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
author_facet Mulyani, Yessy
author_sort Mulyani, Yessy
title IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
title_short IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
title_full IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
title_fullStr IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
title_full_unstemmed IDENTIFIKASI DAN OTENTIFIKASI CITRA WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN SOM DAN KONVOLUSI
title_sort identifikasi dan otentifikasi citra wajah menggunakan jaringan saraf tiruan som dan konvolusi
url https://digilib.itb.ac.id/gdl/view/3105
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