Chronological classification of Ming and Qing dynasty ceramics images based on an enhanced ResNet50 model

To overcome the limitations of expert-dependent and conventional methods in Ming-Qing ceramic chronology analysis, we propose an enhanced ResNet50 model that integrates dual attention mechanisms (channel and self-attention) to amplify discriminative visual features. A reliable dataset of Ming and Qing ceramics was constructed for training and evaluation. Experimental results show that the improved “Ours” model achieves 94.75% accuracy on the test set, a 2.88% improvement over ResNet50, and outperforms advanced models such as VGG16, DenseNet121, and MobileNetV2. Cross-dataset validation indicates that the method shows excellent generalizability for both ceramic type classification and the chronological categorization of other archaeological artifacts. These findings demonstrate that the integration of both channel and self-attention mechanisms effectively resolves the visual feature differences in Ming and Qing ceramics, providing reliable technical support for the digital preservation of cultural heritage. The source code is publicly available at https://github.com/ZhouAlone/ceramic/.