Improving augmented reality with the help of deep learning methods in the tourism industry

  • سال انتشار: 1402
  • محل انتشار: فصلنامه ریاضی و علوم محاسباتی، دوره: 4، شماره: 2
  • کد COI اختصاصی: JR_JMCS-4-2_006
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 140
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نویسندگان

Mehdi Jabbari

Department of computer engineering, Qom university of technology, Qom, Iran

Maryam Amini

Student, Department of computer science, Islamic Azad University, Naragh Branch, Iran

Hossein Malekinezhad

Faculty member, Department of computer science, Islamic Azad University, Naragh Branch, Iran

Zeynab Berahmand

Department of Industrial Engineering, University of Qom, Qom, Iran

چکیده

From an economic point of view, the tourism industry has a special place. Especially in the single-product economy of Iran, it can be used as the best and most optimal alternative to oil. Augmented reality technology is one of the world's newest and most up-to-date applied technologies, highly regarded today. This research focuses on augmented reality and its patterns. This research aims to investigate and develop a practical pattern identification of augmented reality (ar) and its tracking in the tourism industry. Designs are provided by capturing the position and orientation of the device and its location using sensors and Computer vision with screen technology (augmented reality guide). A guide is designed, implemented, and evaluated as an augmented reality application on a mobile phone. The proposed solution has been using deep learning in marker identification. The deep learning architecture used is Yolo, and the proposed method's marker identification results have an accuracy of ۶۸.۷۳ maps

کلیدواژه ها

Deep Learning, Augmented reality, Tourism Industry, Deep Learning Network

اطلاعات بیشتر در مورد COI

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