Yu, X., Zhang, L., & Shen, M. Nantong Blue Calico Image Dataset and Its Recognition. Presentado en. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/CEC55065.2022.9870225
Xiang Yu Li Zhang Mei Shen IEEEBaseline results Benchmark dataset Benchmark datasets Blue calico Classification (of information) Computer Vision Convolutional neural networks Deep learning Image datasets Image recognition Intangible cultural heritage Intangible cultural heritages Large dataset Large-scale datasets Learning systems Nantong Public dataset Public image
Ver
Chen, G. -F. Music sheet score recognition of Chinese Gong-che notation based on Deep Learning. 183-190. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/BDACS53596.2021.00048
G.-F. ChenArtificial intelligence methods Bayes decision theory Big data Chinese traditional music Classification (of information) Clustering analysis Computer music Data handling Decision theory Deep learning Genetic algorithms Gong-che notation Intangible cultural heritages Integrated classification Network layers Semantic information Semantics Similarity measurements Spatiotemporal information Deep learning optical music recognition
Ver
Chen, G. -F. Music sheet score recognition of Chinese Gong-che notation based on Deep Learning. 183-190. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/BDACS53596.2021.00048
G.-F. ChenArtificial intelligence methods Bayes decision theory Big data Chinese traditional music Classification (of information) Clustering analysis Computer music Data handling Decision theory Deep learning Genetic algorithms Gong-che notation Intangible cultural heritages Integrated classification Network layers Semantic information Semantics Similarity measurements Spatiotemporal information Deep learning optical music recognition
Ver
Bakalos, N., Rallis, I., Doulamis, N., Doulamis, A., Voulodimos, A., & Vescoukis, V. Motion Primitives Classification Using Deep Learning Models for Serious Game Platforms. 40, 26-38. https://doi.org/10.1109/MCG.2020.2985035
Nikolaos Bakalos Ioannis Rallis Nikolaos Doulamis Anastasios Doulamis Athanasios Voulodimos Vassilios VescoukisBi-directional analysis Convolution Cultural heritages Deep learning Intangible cultural heritage Intangible cultural heritages Learning systems Long short-term memory Low-cost sensors machine learning Monitoring capabilities Motion Primitives Classification Motion analysis Motion primitives Processing layer Serious Game Serious games Visual information dance
Ver
Dou, J., Qin, J., Jin, Z., & Li, Z. Knowledge graph based on domain ontology and natural language processing technology for Chinese intangible cultural heritage. 48, 19-28. https://doi.org/10.1016/j.jvlc.2018.06.005
Jinhua Dou Jingyan Qin Zanxia Jin Zhuang LiDeep learning Domain ontology Intangible cultural heritage Knowledge graph Natural language processing The 24 solar terms
Ver
Chen, B., Chen, K., & Wang, X. Influence of Internet Information Technology on Deep Learning: A Case of Science Literature. 872-875. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICETCI55101.2022.9832343
B. Chen K. Chen X. WangAnalysis techniques Deep learning Hotspots Internet information internet information technology knowledge hotspot Prosperity warning Research trends Sheng shi wei yan Sheng shi wei yan Text processing Time series analysis Visualization Visualization technique Word of warning to a prosperous age Words of Warning to a Prosperous Age internet information technology knowledge hotspot
Ver
Mehta, S., & Kukreja, V. Heritage Coins Classification: An Federated CNN Approach to Analyse Performance of Global and Client-side Models. 141-146. https://doi.org/10.1109/ICSH57060.2023.10482817
S. Mehta V. KukrejaClassification Client sides convolutional neural network convolutional neural network Convolutional neural networks Deep learning Deep learning Digital preservation Digital storage E-learning F1 scores Federated learning Intangible heritage coin Intangible heritage coins Learning systems Modeling approach Performance Side models Textures Transfer learning
Ver
Mehta, S., & Kukreja, V. Heritage Coins Classification: An Federated CNN Approach to Analyse Performance of Global and Client-side Models. 141-146. https://doi.org/10.1109/ICSH57060.2023.10482817
S. Mehta V. KukrejaClassification Client sides convolutional neural network convolutional neural network Convolutional neural networks Deep learning Deep learning Digital preservation Digital storage E-learning F1 scores Federated learning Intangible heritage coin Intangible heritage coins Learning systems Modeling approach Performance Side models Textures Transfer learning
Ver
Mao, R. EmbrNet: Quantitative Evaluation Model for the Inheritance of Embroidery as an Intangible Cultural Heritage. 1761-1765. https://doi.org/10.1109/AINIT65432.2025.11035726
Rui MaoBenchmarking Cultural value Deep learning Embroidery Historic preservation Human civilization Intangible cultural heritages Model sharing Multi-modelling Personnel training Quantitative evaluation models Social values Textile printing Traditional crafts
Ver
Xuelin, Q., Jue, H., Ying, S., & Zheng, L. Digital Style Design of Nanjing Brocade Based on Deep Learning. 339-342. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCST53801.2021.00077
Q. Xuelin H. Jue S. Ying L. ZhengComponent: nanjing brocade Deep learning Digital methods Digital protection Digitisation E-learning Intangible cultural heritages Nanjing Silk fabrics Style designs Style transfer Textiles component: nanjing brocade Deep learning Digital protection style transfer
Ver