基于cnn的旅游应用分类专门针对文化信息

Takuma Hirotsu, Masaharu Hirota, Tetsu Araki, Masaki Endo, H. Ishikawa
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引用次数: 0

摘要

由于近年来国际游客数量的增加,过度旅游已成为日本的一个重要难题。这种密集的旅游导致了观光问题,因为在旅游区向游客介绍文化和规则的机会很少。需要一些系统来正确地传达旅游区的文化方面。本文提出了一种用卷积神经网络(CNN)从照片中向用户呈现有用信息(如特定区域的文化)的系统。游客可以在观看照片的同时,通过浏览有用的信息,将内容与现实世界联系起来,从而获得信息。在我们构建了原型系统,用英语呈现30种有用的信息后,我们对我们的系统进行了定量评估。我们还对日本和外国居民进行了问卷调查。结果表明,我们的系统有效地促进了外国游客对日本文化和规范的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tourism application with CNN-Based Classification specialized for cultural information
Over-tourism has become an important difficulty in Japan because the number of visiting international tourists has increased in recent years. This intensive tourism leads to sightseeing problems because opportunities to inform tourists about culture and rules in tourist areas are few. Some system is needed to convey correct cultural aspects of tourist areas. This paper proposes a system to present a user with useful information such as area- specific culture from photographs taken with a convolutional neural network (CNN). Tourists can gain information by associating the contents with the real world by browsing useful information while viewing photographs. After we constructed the prototype system to present 30 types of useful information in English, we evaluated our system quantitatively. We also administered a questionnaire survey for Japanese and foreign residents. The results demonstrate that our system is effective to facilitate foreign tourists' understanding Japanese culture and norms.
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