Recognition of notational notation based on convolutional neural network

Zhaoyong Fan; Shuang Chen

doi:10.1117/12.2653861

8 December 2022 Recognition of notational notation based on convolutional neural network

Zhaoyong Fan, Shuang Chen

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124741G (2022) https://doi.org/10.1117/12.2653861
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Aiming at the complex recognition process of numbered musical notes in traditional methods and the low recognition accuracy, a method for recognition of musical notes based on convolutional neural network is proposed. Based on the structural characteristics of the notational notes, a single-input and three-output note recognition network model is established. The convolutional neural network is trained using sample images containing note information labels to obtain a note image recognition model. The training results show that the accuracy of the model and the change trend of the loss value perform well. In order to test the practicability of this method, the numbered musical notes of some songs were recognized and compared with other methods. The results show that this method has high recognition accuracy and fast recognition speed, which proves the validity and practicality of the recognition model.

Citation Download Citation

Zhaoyong Fan and Shuang Chen "Recognition of notational notation based on convolutional neural network", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124741G (8 December 2022); https://doi.org/10.1117/12.2653861

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