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Fine-tunning and knowledge transfer for gender recognition using CNN
Cita
Varga, Thomas Alexandru
(2016).
Fine-tunning and knowledge transfer for gender recognition using CNN.
Tesis (Master), E.T.S. de Ingenieros Informáticos (UPM).
Descripción
| Título: | Fine-tunning and knowledge transfer for gender recognition using CNN |
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| Autor/es: |
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| Director/es: |
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| Tipo de Documento: | Tesis (Master) |
| Título del máster: | Inteligencia Artificial |
| Fecha: | Julio 2016 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S. de Ingenieros Informáticos (UPM) |
| Departamento: | Inteligencia Artificial |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
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.
Más información
| ID de Registro: | 43406 |
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| Identificador DC: | https://oa.upm.es/43406/ |
| Identificador OAI: | oai:oa.upm.es:43406 |
| Depositado por: | Biblioteca Facultad de Informatica |
| Depositado el: | 29 Sep 2016 08:09 |
| Ultima Modificación: | 29 Sep 2016 08:10 |
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