Estradé Albiol, SòniaPozo Bueno, Daniel delRoset Tomàs, Marc2021-10-292021-10-292021-07https://hdl.handle.net/2445/180920Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutors: Sònia Estradé, Daniel Del Pozo BuenoIn this work we test machine learning tools such as the Support Vector Machine algorithm and neural network models on the task of Electron Energy-Loss Spectroscopy (EELS) spectra classification. Given many sample spectra of EELS applied on wüstite and magnetite nanocubes, we train both models to determine the oxidation state of iron. We show that SMV exhibits a good performance on classifying clean data, and we demonstrate the capability of neural networks of producing robust results given shifted data5 p.application/pdfengcc-by-nc-nd (c) Roset, 2021http://creativecommons.org/licenses/by-nc-nd/3.0/es/Aprenentatge automàticEspectroscòpia de pèrdua d'energia d'electronsTreballs de fi de grauMachine learningElectron energy loss spectroscopyBachelor's thesesinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess