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MythicVision:一个基于深度学习的移动应用程序,用于理解印度神话中的神灵,使用以重量为中心的决策方法
Tauseef Khan1, Aditya Nitin Patil2, Aviral Singh2
1School of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, 522237, India. tauseef.khan@vitap.ac.in.
Scientific reports
|January 21, 2025
概括
这项研究介绍了MythicVision,一个深度学习的移动应用程序,帮助外国游客了解印度的神. 它在识别和解释神像方面达到96%的准确性,弥合了文化理解的差距.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 文化遗产研究 文化遗产研究
背景情况:
- 由于文化和信息上的差距,外国游客面临着理解印度神灵的挑战.
- 现有的识别宗教图像的方法缺乏印度神话的专门应用.
研究的目的:
- 开发一个基于深度学习的移动应用程序,MythicVision,用于识别和解释印度神话神灵的图像.
- 通过可访问的技术,增强外国游客对印度丰富的文化遗产的理解.
主要方法:
- 训练和评估四个最先进的深度学习模型,使用一个定制的数据集,包括10970个印度神像.
- 实施以重量为中心的决策机制,使用基于测试准确度的模型智能权重来改进分类.
- 将框架集成到一个端到端的Web应用程序中,以方便用户.
主要成果:
- 在内部数据集上,MythicVision框架实现了96%的准确性.
- 以重量为中心的决策机制在多类图像分类中表现优于传统的多数投票.
- 该应用程序成功地识别和分类实时印度神像图像.
结论:
- MythicVision有效地弥合了对印度神话感兴趣的外国游客的文化理解差距.
- 开发的深度学习方法为神像识别提供了一种新而准确的解决方案.
- 公开发布的应用程序和源代码支持学术和非商业研究.
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