Damage Detection of Guqin in CT Images Based on Deep Neural Network

Yingxi Tang

doi:doi:10.11648/j.ajcst.20220503.15

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Damage Detection of Guqin in CT Images Based on Deep Neural Network

Yingxi Tang

Published in American Journal of Computer Science and Technology (Volume 5, Issue 3)

Received: 25 August 2022 Accepted: 7 September 2022 Published: 27 September 2022

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Abstract

Guqin is the treasure of Chinese heritage culture and the top listed musical instrument. Among the Guqin collected in the Palace Museum, the most famous Guqin named Jiuxiao Huanpei was made by Lei Wei in the Tang Dynasty, which was regarded as an invaluable treasure and ranked first in the Palace Museum. There is a very rare situation in its internal structure where in the Dragon Pool, we saw a round ditch with a width of 2 cm and a depth of 1 cm, there is no such groove in the belly of an ordinary Guqin. This structure has led many well-known modern musical instrument makers to deliberately design their Guqin like this, because they believe that this is the exquisite design of the ancient master, which can make the sound performance better. Few people have questioned it for hundreds of years. Nowadays, the artificial intelligence technology in the world is developing very fast, among which the model used for object detection has gradually improved its accuracy. This paper applies the YOLO model in deep learning to train with 7803 CT slices of Guqin, and then tests the Jiuxiao Huanpei Guqin in the Forbidden City and several other Guqins. The conclusion is that this Guqin was not intended to be designed to that model, it was likely damaged, and like the Emperor’s New Clothes, no one except AI can tell the truth. The purpose of this paper is to arouse people's attention to the establishment of digital scientific analysis for cultural heritage.

Published in	American Journal of Computer Science and Technology (Volume 5, Issue 3)
DOI	10.11648/j.ajcst.20220503.15
Page(s)	184-189
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Guqin, CT, 3D, Deep Neural Network, YOLO

References

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APA Style

Yingxi Tang. (2022). Damage Detection of Guqin in CT Images Based on Deep Neural Network. American Journal of Computer Science and Technology, 5(3), 184-189. https://doi.org/10.11648/j.ajcst.20220503.15

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ACS Style

Yingxi Tang. Damage Detection of Guqin in CT Images Based on Deep Neural Network. Am. J. Comput. Sci. Technol. 2022, 5(3), 184-189. doi: 10.11648/j.ajcst.20220503.15

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AMA Style

Yingxi Tang. Damage Detection of Guqin in CT Images Based on Deep Neural Network. Am J Comput Sci Technol. 2022;5(3):184-189. doi: 10.11648/j.ajcst.20220503.15

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@article{10.11648/j.ajcst.20220503.15,
  author = {Yingxi Tang},
  title = {Damage Detection of Guqin in CT Images Based on Deep Neural Network},
  journal = {American Journal of Computer Science and Technology},
  volume = {5},
  number = {3},
  pages = {184-189},
  doi = {10.11648/j.ajcst.20220503.15},
  url = {https://doi.org/10.11648/j.ajcst.20220503.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20220503.15},
  abstract = {Guqin is the treasure of Chinese heritage culture and the top listed musical instrument. Among the Guqin collected in the Palace Museum, the most famous Guqin named Jiuxiao Huanpei was made by Lei Wei in the Tang Dynasty, which was regarded as an invaluable treasure and ranked first in the Palace Museum. There is a very rare situation in its internal structure where in the Dragon Pool, we saw a round ditch with a width of 2 cm and a depth of 1 cm, there is no such groove in the belly of an ordinary Guqin. This structure has led many well-known modern musical instrument makers to deliberately design their Guqin like this, because they believe that this is the exquisite design of the ancient master, which can make the sound performance better. Few people have questioned it for hundreds of years. Nowadays, the artificial intelligence technology in the world is developing very fast, among which the model used for object detection has gradually improved its accuracy. This paper applies the YOLO model in deep learning to train with 7803 CT slices of Guqin, and then tests the Jiuxiao Huanpei Guqin in the Forbidden City and several other Guqins. The conclusion is that this Guqin was not intended to be designed to that model, it was likely damaged, and like the Emperor’s New Clothes, no one except AI can tell the truth. The purpose of this paper is to arouse people's attention to the establishment of digital scientific analysis for cultural heritage.},
 year = {2022}
}

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TY  - JOUR
T1  - Damage Detection of Guqin in CT Images Based on Deep Neural Network
AU  - Yingxi Tang
Y1  - 2022/09/27
PY  - 2022
N1  - https://doi.org/10.11648/j.ajcst.20220503.15
DO  - 10.11648/j.ajcst.20220503.15
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 184
EP  - 189
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20220503.15
AB  - Guqin is the treasure of Chinese heritage culture and the top listed musical instrument. Among the Guqin collected in the Palace Museum, the most famous Guqin named Jiuxiao Huanpei was made by Lei Wei in the Tang Dynasty, which was regarded as an invaluable treasure and ranked first in the Palace Museum. There is a very rare situation in its internal structure where in the Dragon Pool, we saw a round ditch with a width of 2 cm and a depth of 1 cm, there is no such groove in the belly of an ordinary Guqin. This structure has led many well-known modern musical instrument makers to deliberately design their Guqin like this, because they believe that this is the exquisite design of the ancient master, which can make the sound performance better. Few people have questioned it for hundreds of years. Nowadays, the artificial intelligence technology in the world is developing very fast, among which the model used for object detection has gradually improved its accuracy. This paper applies the YOLO model in deep learning to train with 7803 CT slices of Guqin, and then tests the Jiuxiao Huanpei Guqin in the Forbidden City and several other Guqins. The conclusion is that this Guqin was not intended to be designed to that model, it was likely damaged, and like the Emperor’s New Clothes, no one except AI can tell the truth. The purpose of this paper is to arouse people's attention to the establishment of digital scientific analysis for cultural heritage.
VL  - 5
IS  - 3
ER  -

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Author Information

Yingxi Tang

National Remote Sensing Lab., Zhicheng International Academy, Beijing, China

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APA Style

Yingxi Tang. (2022). Damage Detection of Guqin in CT Images Based on Deep Neural Network. American Journal of Computer Science and Technology, 5(3), 184-189. https://doi.org/10.11648/j.ajcst.20220503.15

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ACS Style

Yingxi Tang. Damage Detection of Guqin in CT Images Based on Deep Neural Network. Am. J. Comput. Sci. Technol. 2022, 5(3), 184-189. doi: 10.11648/j.ajcst.20220503.15

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AMA Style

Yingxi Tang. Damage Detection of Guqin in CT Images Based on Deep Neural Network. Am J Comput Sci Technol. 2022;5(3):184-189. doi: 10.11648/j.ajcst.20220503.15

Copy | Download

@article{10.11648/j.ajcst.20220503.15,
  author = {Yingxi Tang},
  title = {Damage Detection of Guqin in CT Images Based on Deep Neural Network},
  journal = {American Journal of Computer Science and Technology},
  volume = {5},
  number = {3},
  pages = {184-189},
  doi = {10.11648/j.ajcst.20220503.15},
  url = {https://doi.org/10.11648/j.ajcst.20220503.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20220503.15},
  abstract = {Guqin is the treasure of Chinese heritage culture and the top listed musical instrument. Among the Guqin collected in the Palace Museum, the most famous Guqin named Jiuxiao Huanpei was made by Lei Wei in the Tang Dynasty, which was regarded as an invaluable treasure and ranked first in the Palace Museum. There is a very rare situation in its internal structure where in the Dragon Pool, we saw a round ditch with a width of 2 cm and a depth of 1 cm, there is no such groove in the belly of an ordinary Guqin. This structure has led many well-known modern musical instrument makers to deliberately design their Guqin like this, because they believe that this is the exquisite design of the ancient master, which can make the sound performance better. Few people have questioned it for hundreds of years. Nowadays, the artificial intelligence technology in the world is developing very fast, among which the model used for object detection has gradually improved its accuracy. This paper applies the YOLO model in deep learning to train with 7803 CT slices of Guqin, and then tests the Jiuxiao Huanpei Guqin in the Forbidden City and several other Guqins. The conclusion is that this Guqin was not intended to be designed to that model, it was likely damaged, and like the Emperor’s New Clothes, no one except AI can tell the truth. The purpose of this paper is to arouse people's attention to the establishment of digital scientific analysis for cultural heritage.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Damage Detection of Guqin in CT Images Based on Deep Neural Network
AU  - Yingxi Tang
Y1  - 2022/09/27
PY  - 2022
N1  - https://doi.org/10.11648/j.ajcst.20220503.15
DO  - 10.11648/j.ajcst.20220503.15
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 184
EP  - 189
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20220503.15
AB  - Guqin is the treasure of Chinese heritage culture and the top listed musical instrument. Among the Guqin collected in the Palace Museum, the most famous Guqin named Jiuxiao Huanpei was made by Lei Wei in the Tang Dynasty, which was regarded as an invaluable treasure and ranked first in the Palace Museum. There is a very rare situation in its internal structure where in the Dragon Pool, we saw a round ditch with a width of 2 cm and a depth of 1 cm, there is no such groove in the belly of an ordinary Guqin. This structure has led many well-known modern musical instrument makers to deliberately design their Guqin like this, because they believe that this is the exquisite design of the ancient master, which can make the sound performance better. Few people have questioned it for hundreds of years. Nowadays, the artificial intelligence technology in the world is developing very fast, among which the model used for object detection has gradually improved its accuracy. This paper applies the YOLO model in deep learning to train with 7803 CT slices of Guqin, and then tests the Jiuxiao Huanpei Guqin in the Forbidden City and several other Guqins. The conclusion is that this Guqin was not intended to be designed to that model, it was likely damaged, and like the Emperor’s New Clothes, no one except AI can tell the truth. The purpose of this paper is to arouse people's attention to the establishment of digital scientific analysis for cultural heritage.
VL  - 5
IS  - 3
ER  -

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