Next Article in Journal
Staff, Symbol and Melody Detection of Medieval Manuscripts Written in Square Notation Using Deep Fully Convolutional Networks
Next Article in Special Issue
Generation of Melodies for the Lost Chant of the Mozarabic Rite
Previous Article in Journal
Experimental Study on Dynamic Response Characteristics of RPC and RC Micro Piles in SAJBs
Previous Article in Special Issue
16th Sound and Music Computing Conference SMC 2019 (28–31 May 2019, Malaga, Spain)
Article

State-of-the-Art Model for Music Object Recognition with Deep Learning

Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(13), 2645; https://doi.org/10.3390/app9132645
Received: 23 May 2019 / Revised: 11 June 2019 / Accepted: 26 June 2019 / Published: 29 June 2019
(This article belongs to the Special Issue Sound and Music Computing -- Music and Interaction)
Optical music recognition (OMR) is an area in music information retrieval. Music object detection is a key part of the OMR pipeline. Notes are used to record pitch and duration and have semantic information. Therefore, note recognition is the core and key aspect of music score recognition. This paper proposes an end-to-end detection model based on a deep convolutional neural network and feature fusion. This model is able to directly process the entire image and then output the symbol categories and the pitch and duration of notes. We show a state-of-the-art recognition model for general music symbols which can get 0.92 duration accurary and 0.96 pitch accuracy . View Full-Text
Keywords: optical music recognition; deep learning; object detection; note recognition optical music recognition; deep learning; object detection; note recognition
Show Figures

Figure 1

MDPI and ACS Style

Huang, Z.; Jia, X.; Guo, Y. State-of-the-Art Model for Music Object Recognition with Deep Learning. Appl. Sci. 2019, 9, 2645. https://doi.org/10.3390/app9132645

AMA Style

Huang Z, Jia X, Guo Y. State-of-the-Art Model for Music Object Recognition with Deep Learning. Applied Sciences. 2019; 9(13):2645. https://doi.org/10.3390/app9132645

Chicago/Turabian Style

Huang, Zhiqing, Xiang Jia, and Yifan Guo. 2019. "State-of-the-Art Model for Music Object Recognition with Deep Learning" Applied Sciences 9, no. 13: 2645. https://doi.org/10.3390/app9132645

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop