Bronze inscription recognition with distribution calibration based on few-shot learning

Yi Zheng; Yunfeng Yan; Donglian Qi

doi:10.1117/12.2627100

14 February 2022 Bronze inscription recognition with distribution calibration based on few-shot learning

Yi Zheng, Yunfeng Yan, Donglian Qi

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 121610O (2022) https://doi.org/10.1117/12.2627100
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

Bronze inscription is one of the earliest well-established writing systems dating back to Shang dynasty in China. The Recognition of Bronze character recognition plays an important role in the identification and interpretation of Bronze inscription which traditionally is a tough and challenging task. To deal with class imbalance of training data in bronze inscription recognition, we propose a method based on few-shot learning. The recognition process consists of three stages. In the first stage, a model is pretrained in a large-scale character dataset with a novel negative margin loss. In the second stage, the pretrained weights of the backbone network is transferred to the target dataset. In the final stage, the distribution of few-shot classes is calibrated and a new classifier is re-trained accordingly. Through qualitative and quantitative experimental analyses, the proposed method exceeds the state-of-the-art on our Bronze Character dataset.

Citation Download Citation

Yi Zheng, Yunfeng Yan, and Donglian Qi "Bronze inscription recognition with distribution calibration based on few-shot learning", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 121610O (14 February 2022); https://doi.org/10.1117/12.2627100

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