# AI Mobile Application for Archaeological Dating of Bronze Dings

arXiv: https://arxiv.org/abs/2401.01002 · HTML: https://mlsanity.com/paper/2401.01002/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 5 references that are in the map.
- First posted on arXiv 5 Sep 2023.

## Builds on (most cited first, 3 of 3)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [A ConvNet for the 2020s](https://mlsanity.com/paper/2201.03545/) (2022)
- [Sparse R-CNN: End-to-End Object Detection with Learnable Proposals](https://mlsanity.com/paper/2011.12450/) (2020)

## Built on by (most cited first, 1 of 1)

- [ShiftedBronzes: Benchmarking and Analysis of Domain Fine-Grained Classification in Open-World Settings](https://mlsanity.com/paper/2412.12683/) (2024)

## Abstract (arXiv)

We develop an AI application for archaeological dating of bronze Dings. A classification model is employed to predict the period of the input Ding, and a detection model is used to show the feature parts for making a decision of archaeological dating. To train the two deep learning models, we collected a large number of Ding images from published materials, and annotated the period and the feature parts on each image by archaeological experts. Furthermore, we design a user system and deploy our pre-trained models based on the platform of WeChat Mini Program for ease of use. Only need a smartphone installed WeChat APP, users can easily know the result of intelligent archaeological dating, the feature parts, and other reference artifacts, by taking a photo of a bronze Ding. To use our application, please scan this QR code by WeChat.