A web scrapping and AI approach for archeologists to analyze the ancient cities
Author:
DEMİR Nusret1ORCID, BOYOĞLU Cem Sönmez2ORCID, KAYIKCI Deniz3ORCID
Affiliation:
1. AKDENIZ UNIVERSITY 2. WUHAN UNIVERSITY 3. Universitat Autonomous De Barcelona
Abstract
Studies on machine learning have started to reach a level where we can save a great amount of time and labor by producing structures that can think as a human and have decisions. Deep learning, one of the methods of machine learning, is an artificial intelligence-training technique that can predict the outputs from the given dataset In this study, the use of web scraping technique was investigated to determine the potential of identifying ancient columns, which are one of the most important architectural elements of cultural heritage, by artificial intelligence. In this study, web scraping approach is presented as a digital data acquisition method for archaeology field to collect imagery datasets from web to analyze the ancient cities. For analysis, a free online, and easy-to-use tool ‘Amazon Rekognation’ is used for comparing the number of columns found in the scrapped images. For summarizing the research, simply, we have tried to get the answer the question from PC that ‘which site has the columns most, Perge, Xanthos or Phaselis?’. With this proposed approach, the archeologists can have a primarily knowledge about the sites they will study with use of operational tools for their further comprehensive research.
Funder
Koc University Suna & İnan Kıraç Research Center for Mediterranean Civilizations
Publisher
Mersin University
Reference20 articles.
1. Kintigh, K. W., Altschul, J. H., Beaudry, M. C., Drennan, R. D., Kinzig, A. P., Kohler, T. A., Limp, W. F., Maschner, H. D. G., Michener, W. K., Pauketat, T. R., Peregrine, P., Sabloff, J. A., Wilkinson, T. J., Wright, H. T., & Zeder, M. A. (2014). Grand challenges for archaeology. Proceedings of the National Academy of Sciences, 111(3), 879–880. https://doi.org/10.1073/PNAS.1324000111 2. Barceló, J. A. (2010, January). Computational intelligence in archaeology. State of the art. In Making History Interactive. Computer Applications and Quantitative Methods in Archaeology (CAA). Proceedings of the 37th International Conference (Vol. 11, p. 21). Williamsburg, Virginia, United States of America: Archaeopress. 3. Kan, M. H., Keskin, H., Demir, N., Selim, S., Aslan, E., & Güneş, N. (2022). A Preliminary Field Work on Digital Heritage and the Use of Virtual Reality for Cultural Heritage Management. Advances in Hospitality and Tourism Research (AHTR), 10(4), 625-645. 4. Korumaz, A. G., Dülgerler, O. N., & Yakar, M. (2011). Kültürel mirasin belgelenmesinde dijital yaklaşimlar. Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 26(3), 67-83. 5. Ulvi, A., Yakar, M., Yiğit, A., & Kaya, Y. (2019). The use of photogrammetric techniques in documenting cultural heritage: The Example of Aksaray Selime Sultan Tomb. Universal Journal of Engineering Science, 7(3), 64-73.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|