Please use this identifier to cite or link to this item: https://dipositint.ub.edu/dspace/handle/2445/197741
Title: Una revisió de neural style transfer
Author: Puch Camacho, Gerard
Director/Tutor: García Marcos, Eloy
Keywords: Xarxes neuronals convolucionals
Processament digital d'imatges
Programari
Treballs de fi de grau
Sistemes classificadors (Intel·ligència artificial)
Convolutional neural networks
Digital image processing
Computer software
Learning classifier systems
Bachelor's theses
Issue Date: 13-Jun-2022
Abstract: [en] In recent years, a technology has emerged, capable of simulating human reasoning and performing complex tasks that conventional programming was unable to perform. We are talking about neural networks, Deep Learning algorithms that are used in many different fields and with many good results, such as: prediction of successes and simulations of all kinds, recognition and classification of elements, data processing and modeling, control engineering, artificial intelligence, facial recognition; and many more. In this work we will focus on a specific type of network, convolutional neural networks, capable of interpreting and classifying images. We will study in depth and review the problem of Style Transfer through this neural technology. Thus differentiating two phases in the work, a phase of investigation and research and a practical phase where to implement and experiment with this technology. Finally, an analysis of the operation, performance, and efficiency of this technology will be performed and an assessment will be made.
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Eloy García Marcos
URI: https://hdl.handle.net/2445/197741
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica

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