FENG Jinniu 1, ZHOU Qiang 1, ZHANG Ruirui 1, WANG Ying 2, LUO Hongjie 2, 3
(1. School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an710021,Shaanxi,China;2. Research Institute of Silicate Cultural Heritage, Shaanxi University of Science & Technology, Xi’an 710021,Shaanxi, China; 3. School of Material Science and Engineering, Shanghai University, Shanghai 200444, China)
Abstract: Chinese ancient ceramics are characterized by exquisite craftsmanship, rich variety, unique artistic charm and cultural connotation. Therefore, scientific identification of ancient ceramics has always been the focus of cultural relic identification research. Noting the shortcomings of the current dating methods for ancient ceramics, in the context of artificial intelligence, a novel approach to classify and identify the dating of the ancient ceramic artifacts by using convolution neural network of deep learning was proposed. The method breaks the technical bottleneck that "the characteristic quantity of ancient ceramics depends on manual determination". Experiment results demonstrate that the accuracy of this method for classification and dating of ancient ceramics is 96.37%, making it an effective auxiliary method for dating ancient ceramics.
Key words: chronological identification of ancient ceramics; convolutional neural network (CNN); deep learning