Tourism application with CNN-Based Classification specialized for cultural information-Reference-Cited by-同舟云学术

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Tourism application with CNN-Based Classification specialized for cultural information

Published:2019-12-02 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services
language:
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Author:

Hirotsu Takuma¹,Hirota Masaharu²,Araki Tetsuya³,Endo Masaki⁴,Ishikawa Hiroshi¹

Affiliation:

1. Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo Japan

2. Department of Information Science, Okayama University of Science, Okayama Japan

3. Graduate School of Science and Technology, Gunma University, Gunma Japan

4. Polytechnic University, Tokyo Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3366030.3366073

Reference23 articles.

1. Conceptual Design of a hybrid Participatory IT supporting in-situ and ex-situ collaborative text authoring

2. Aworldwide tourism recommendation system based on geotaggedweb photos

3. Experiences of developing and deploying a context-aware tourist guide

5. G. Gando T. Yamada H. Sato S. Oyama and M. Kurihara. Fine-tuning deep convolutional neural networks for distinguishing illustrations from photographs. Expert Syst. Appl. 66(C):295--301 Dec. 2016. G. Gando T. Yamada H. Sato S. Oyama and M. Kurihara. Fine-tuning deep convolutional neural networks for distinguishing illustrations from photographs. Expert Syst. Appl. 66(C):295--301 Dec. 2016.

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1. Assessing tourism capital using two-tiered empirical model;Annals of Tourism Research Empirical Insights;2024-11

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