<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Advances in AI and VR have enhanced digital virtual interaction, crucial for preserving wood carving art. This study introduces an optimized system using intelligent image recognition, overcoming challenges in current systems. It involves image collection, noise reduction, feature extraction, normalization, and transfer learning-based model training. The system achieved a 93.34% recognition accuracy, surpassing traditional methods and improving overall performance.</p>
</abstract>

Advances in AI and VR have enhanced digital virtual interaction, crucial for preserving wood carving art. This study introduces an optimized system using intelligent image recognition, overcoming challenges in current systems. It involves image collection, noise reduction, feature extraction, normalization, and transfer learning-based model training. The system achieved a 93.34% recognition accuracy, surpassing traditional methods and improving overall performance.

Research on Digital Virtual Interaction Technology for Intelligent Image Recognition in Woodcarving Protection

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Advances in AI and VR have enhanced digital virtual interaction, crucial for preserving wood carving art. This study introduces an optimized system using...

Research on Digital Virtual Interaction Technology for Intelligent Image Recognition in Woodcarving Protection

Online veröffentlicht: 20. Apr. 2024

Seitenbereich: -

Eingereicht: 03. Apr. 2024

Akzeptiert: 09. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0848

Schlüsselwörter
Wood Carving Protection, Intelligent Image Recognition, Digital Virtual Interaction, Feature Extraction, Transfer Learning

© 2024 Xinyong Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Digital Virtual Interaction Technology for Intelligent Image Recognition in Woodcarving Protection

Online veröffentlicht: 20. Apr. 2024

Seitenbereich: -

Eingereicht: 03. Apr. 2024

Akzeptiert: 09. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0848

SchlüsselwörterWood Carving Protection, Intelligent Image Recognition, Digital Virtual Interaction, Feature Extraction, Transfer Learning

© 2024 Xinyong Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Wood Carving Protection, Intelligent Image Recognition, Digital Virtual Interaction, Feature Extraction, Transfer Learning