Fine-tunning and knowledge transfer for gender recognition using CNN

Varga, Thomas Alexandru (2016). Fine-tunning and knowledge transfer for gender recognition using CNN. Thesis (Master thesis), E.T.S. de Ingenieros Informáticos (UPM).

Description

Title: Fine-tunning and knowledge transfer for gender recognition using CNN
Author/s:
  • Varga, Thomas Alexandru
Contributor/s:
  • Baumela Molina, Luis
Item Type: Thesis (Master thesis)
Masters title: Inteligencia Artificial
Date: July 2016
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Automatic gender classification has gain popularity particularly with the increasing amount of social platforms and social media providers. Also, recently has been noted an increase use of CNNs to solve different classification tasks, one of which is gender recognition. Training and testing a CNN often involves a large amount of time and the classification results are not consistent across databases. In this work I use a pre-trained CNN with one data set, retrain it in order to obtain similar result when classifying another data set with much less effort involve in training. I evaluate the method using the Image of Group data set with a CNN trained with Adience data set.

More information

Item ID: 43406
DC Identifier: http://oa.upm.es/43406/
OAI Identifier: oai:oa.upm.es:43406
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 29 Sep 2016 08:09
Last Modified: 29 Sep 2016 08:10
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