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http://hdl.handle.net/2445/119796
Title: | Study of reconstruction ICA for feature extraction in images and signals |
Author: | Beltrán Segarra, Marc |
Director/Tutor: | Igual Muñoz, Laura |
Keywords: | Xarxes neuronals (Informàtica) Aprenentatge automàtic Programari Treballs de fi de grau Algorismes computacionals Neural networks (Computer science) Machine learning Computer software Bachelor's theses Computer algorithms |
Issue Date: | 22-Jun-2017 |
Abstract: | [en] During the last years, neural networks have become a vehicular discipline in the field of machine learning. At the same time, classical machine learning methods have become easier to use due to the availability of higher computational power. The goal of this project is to reconstruct a classical machine learning algorithm used for feature and source extraction (ICA) using neural networks. This reconstruction could bypass some of the drawbacks presents when using ICA. We have studied how the reconstruction operates under different conditions and performed a comparison with the classical algorithm that we reconstructed. |
Note: | Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Laura Igual Muñoz |
URI: | http://hdl.handle.net/2445/119796 |
Appears in Collections: | Programari - Treballs de l'alumnat Treballs Finals de Grau (TFG) - Enginyeria Informàtica |
Files in This Item:
File | Description | Size | Format | |
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codi_font.zip | Codi font | 26.88 MB | zip | View/Open |
memoria.pdf | Memòria | 2.52 MB | Adobe PDF | View/Open |
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