arXiv cs.CY· Andrius Tamosiunas, Simone Mozzon, David Bacon, Caroline Cox, Alan Collins·· 12 小时前AI 评分24
用机器学习自动识别象牙雕刻：检测非法野生动物贸易的概念验证
Automated identification of ivory carvings using machine learning: A proof-of-concept approach to detecting the illegal wildlife trade
AI 导读
研究团队用 U-Net 架构搭配 ResNet34 骨干的语义分割框架，在 541 张原始图像增强数据集上迁移学习，尝试从照片中区分象牙与骨骼制品。在独立测试集上，分类器对高置信样本取得 0.81 的 AUC 和 81% 的整体准确率。该概念验证旨在为执法部门筛查线上市场海量图片、识别非法象牙交易提供自动化图像识别基础。
正文
Abstract:Despite a ban on the international trading of recently poached ivory, elephants are still killed for their tusks. Ivory and its products are mainly sold in online marketplaces. However, due to the huge volume and variety of adverts and the similarity of ivory with other materials that can be legally sold, it is hard for enforcement officials to identify illicit trading and prosecute sellers. Existing techniques for identifying elephant ivory, such as Fourier-transform infrared spectroscopy and microscopy, can reliably distinguish ivory from other materials, but require physical access to the item and cannot be applied to photographs alone. As a result, these methods are unsuitable for screening the large volume of images posted in online marketplaces, leaving a gap for automated, image-based identification tools. In this proof of concept work, we investigate the potential of machine learning techniques for image analysis to automatically distinguish ivory objects from bone. We employ a semantic segmentation framework using a U-Net architecture with a ResNet34 backbone, leveraging transfer learning on an augmented dataset of 541 original images. Using a dataset of images of ivory and items resembling carved ivory, several models were trialled. On a distinct test set, the classifier achieved an Area Under the Curve (AUC) of 0.81 and an overall classification accuracy of 81% on confident samples. The paper presents the best-performing model as a proof of concept for developing a system that can effectively identify ivory and its products when indicative features of elephant ivory are present in an image. This work provides initial steps towards a machine learning-based framework designed to advise law-enforcement in detecting illegal elephant ivory trade.
| Comments: | 16 pages, 7 figures and 2 tables. Submitted for publication in PLOS One |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Computers and Society (cs.CY); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.33243 [cs.CV] |
| (or arXiv:2610.33243v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2610.33243 arXiv-issued DOI via DataCite |
Submission history
From: Andrius Tamosiunas [view email]
[v1]
Fri, 23 Oct 2026 19:45:43 UTC (2,007 KB)
来源：arXiv cs.CY · arxiv.org