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Fine-tunning and knowledge transfer for gender recognition using CNN
Citation
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 |
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| Author/s: |
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| 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 |
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 |
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| DC Identifier: | https://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 |
