Document type

Bachelor thesis

Publication date

Publication license

cc-by-nc-nd (c) Guillem Brasó Andilla, 2018
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/125161

Attribution methods for deep convolutional networks

Journal Title

Journal ISSN

Volume Title

Related resource

Abstract

[en] In recent years, Deep Learning has shown great success across several areas. However, even, though it might provide remarkable accuracy for many tasks, its application in some fields faces a fundamental problem: its predictions are not interpretable. Attribution Methods offer a possible solution in regards to this problem. To do so, they resource to results in Game Theory in order to explain individual decisions made by Deep Learning algorithms. In this work, we will be focusing, specifically, on the application of Attribution Techniques to a subset of Deep Learning algorithms: Convolutional Neural Networks.

Description

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Jordi Vitrià i Marca

Citation

Citation

BRASÓ ANDILLA, Guillem. Attribution methods for deep convolutional networks. [consulted: 6 of June of 2026]. Available at: https://hdl.handle.net/2445/125161

Export metadata

JSON - METS

Share record