一个双模块系统,用于在教育材料中推无版权图像和检测侵权
Yeongha Kim1, Soyeon Kim1, Seonghyun Min1
1R&D Center, AIDEEP Co., Ltd., 25, 7na-gil Gwacheon-daero, Gwacheon-si 13840, Republic of Korea.
Journal of imaging
|November 26, 2024
概括
教师现在可以通过新的AI系统避免侵犯版权. 该工具可以检测未经授权的图像使用,并建议无版权的替代方案,确保教育材料的法律合规性.
科学领域:
- 人工智能的人工智能
- 教育技术的教育技术
- 版权法 版权法 版权法
背景情况:
- 图像对于教育至关重要,但存在版权风险.
- 未经授权的图像使用导致教育工作者面临法律挑战.
- 现有的图像版权验证解决方案是不够的.
研究的目的:
- 为教育工作者开发一个双模块的人工智能系统,以检测图像版权侵权.
- 为了提供一个无的解决方案,寻找无版权的替代图像.
- 在创建教育内容时加强法律合规性.
主要方法:
- 一个使用Convolutional Variational Autoencoder (CVAE) 的版权侵权检测模块.
- 一个采用基于Vision Transformer (ViT) 的哈希模型的图像检索模块.
- 使用基准数据集 (Flickr25k) 进行系统评估,并与教育工作者进行用户研究.
主要成果:
- 该系统在Flickr25k数据集上实现了0.812的平均平均精度 (mAP).
- 一项针对65名教师的用户研究显示,他们对版权检测和易用性的满意度很高.
- 该系统有效地识别出侵犯版权的行为,并建议合适的替代方案.
结论:
- 开发的双模块系统成功地解决了教育工作者的版权侵权问题.
- 这种由人工智能驱动的工具有助于创建符合法律要求的教育材料.
- 该系统为教育中的版权管理提供了一个实用和用户友好的解决方案.
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