Carnicer González, ArturoMitjans Coma, Albert2020-10-212020-10-212020-06https://hdl.handle.net/2445/171413Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2020, Tutor: Artur CarnicerIn this paper, we use deep learning to study high-level features for guitar chord detection. In particular, the goal of this project is to build a neural network capable of recognizing finger patterns on the frets of a guitar. Given an input image, the network is able to identify fingers, frets, strings and the corresponding chord. Using a 2-stack Hourglass network for the detection and applying a post-processing algorithm to its corresponding output heatmaps, a 97% accuracy on the detection of chords of 205 different images is obtained5 p.application/pdfengcc-by-nc-nd (c) Mitjans, 2020http://creativecommons.org/licenses/by-nc-nd/3.0/es/Música per a guitarraXarxes neuronals (Informàtica)Treballs de fi de grauGuitar musicNeural networks (Computer science)Bachelor's thesesinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess