Classification of guitar tab and numbered musical notation using ResNet50 network

Hangfei Ma; Liumei Zhang; Yu Han

doi:10.1117/12.2684610

21 July 2023 Classification of guitar tab and numbered musical notation using ResNet50 network

Hangfei Ma, Liumei Zhang, Yu Han

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127172P (2023) https://doi.org/10.1117/12.2684610
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

With the advancement of deep learning and the growth of AI, a new concept for classifying music score images has been introduced. This paper presents a classification method for guitar tabs and numbered musical notation based on the ResNet50 network. The ResNet50 residual network model is used to extract features from music score images, and then the classification is performed based on the recognition probability. Results of the experiments indicate that the recognition accuracy of this model can reach 99.154%, suggesting that the ResNet50 network-based classification method holds good research potential in music score image classification.

Citation Download Citation

Hangfei Ma, Liumei Zhang, and Yu Han "Classification of guitar tab and numbered musical notation using ResNet50 network", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127172P (21 July 2023); https://doi.org/10.1117/12.2684610

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KEYWORDS

Mathematical optimization

Image classification

Image processing

Process modeling

Feature extraction

Convolution

Deep learning

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