Qualitative analysis through visual interpretability techniques of neural network models for mammography classification

Rodríguez Sampayo, Marta. (2021). Qualitative analysis through visual interpretability techniques of neural network models for mammography classification Master Thesis, Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial

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Título Qualitative analysis through visual interpretability techniques of neural network models for mammography classification
Autor(es) Rodríguez Sampayo, Marta
Abstract Nowadays, research in the field of artificial intelligence is focusing on the explainability of the developed algorithms, mainly neural networks. This trend is known as XAI and brings certain advantages such as increased confidence in the decision-making process, improved capacity for error analysis, verification of results and possibility of model refinement, among others. In this work we have focused on interpreting the predictions of recently developed deep learning models through different visualization techniques. The use case we introduce is the detection of breast cancer through the classification of mammographies, since the medical field is widely benefited by the contributions of XAI methods. Furthermore, the target neural networks are based on recent and poorly explored architectures. These are the Vision Transformer model, built through attention blocks, and EfficientNet, designed to improve the performance of convolutional networks.
Notas adicionales Trabajo de Fin de Máster Universitario en Investigación en Inteligencia Artificial. UNED
Materia(s) Ingeniería Informática
Palabra clave Explainable Artificial Intelligence
interpretability
Deep Learning
EfficientNet
vision transformer
mammography
Editor(es) Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial
Director/Tutor Rincón Zamorano, Mariano
Fecha 2021-09-01
Formato application/pdf
Identificador bibliuned:master-ETSInformatica-IIA-Mrodriguez
http://e-spacio.uned.es/fez/view/bibliuned:master-ETSInformatica-IIA-Mrodriguez
Idioma eng
Versión de la publicación acceptedVersion
Nivel de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de recurso master Thesis
Tipo de acceso Acceso abierto

 
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Creado: Mon, 03 Oct 2022, 20:08:04 CET