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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
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Xu, F., & Zhiwei, L. Design method of intangible cultural products based on pharma industries ethics education among educators. 27, 32-41. https://doi.org/10.5912/jcb1035
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Nikolaos Bakalos Ioannis Rallis Nikolaos Doulamis Anastasios Doulamis Eftychios Protopapadakis Athanasios VoulodimosAI for Serious Games Background subtraction Classification performance Convolution Convolutional neural networks convolutional neural network Data set Deep neural networks Gesture recognition Intangible cultural heritage Intangible cultural heritages Learning schemes Moving averages Neural networks Posture identification Serious games Virtual reality
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Putra, F. A., Jamil, D. A. C., Prabandanu, B. A., Faruq, S., Pradana, F. A., Alya, R. F., et al. (2021). Classification of Batik Authenticity Using Convolutional Neural Network Algorithm with Transfer Learning Method. Presented at the. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICIC54025.2021.9632937
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