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

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 84

فایل این مقاله در 13 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JMCS-4-2_006

تاریخ نمایه سازی: 14 آبان 1402

چکیده مقاله:

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

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

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Z. Cao, T. Simon, S. E. Wei, Y. Sheikh, Realtime ...
  • C. Chen, A. Seff, A. Kornhauser, J. Xiao, Deepdriving: Learning ...
  • D. Chen, S. Ren, Y. Wei, X. Cao, J.Sun. Joint ...
  • X. Chen, H. Ma, J. Wan, B. Li, T. Xia, ...
  • N. Dalal, B. Triggs, Histograms of oriented gradients for human ...
  • P. Dollar, C. Wojek, B. Schiele, P. Perona, Pedestrian detection: ...
  • A. Dundar, J. Jin, B. Martini, E. Culurciello, Embedded streaming ...
  • M. Everingham, The PASCAL visual object classes challenge ۲۰۰۹ (VOC۲۰۰۹) ...
  • PF. Felzenszwalb, RB. Girshick, D. McAllester, D. Ramanan. Object detection ...
  • R. Girshick, J.Donahue, T.Darrell, J.Malik, Rich feature hierarchies for accurate ...
  • GE. Hinton, N.Srivastava, A. Krizhevsky, I. Sutskever, RR. Salakhutdinov, Improving ...
  • SH. Hsu, HT. Hung, YQ. Lin, CM. Chang, Defect inspection ...
  • S. Ioffe, C. Szegedy, Batch normalization: Accelerating deep network training ...
  • Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, ...
  • H. Jiang, E. Learned-Miller, Face detection with the faster R-CNN. ...
  • K. Kavukcuoglu, P. Sermanet, YL. Boureau, K. Gregor, M. Mathieu, ...
  • H. Kobatake, Y. Yoshinaga, Detection of spicules on mammogram based ...
  • A. Kontogianni, E. Alepis, C. Patsakis. Smart tourism and artificial ...
  • A. K rizhevsky, I. Sutskever, G.E. Hinton, Image Net classification ...
  • Y. LeCun, Y. Bengio, G. Hinton, Deep learning, Nature, ۵۲۱(۷۵۵۳) ...
  • W. Li, J. Wang, M. Liu, S. Zhao, X. Ding, ...
  • C. Liu, H. Zhu, D. Tang, Q. Nie, T. Zhou, ...
  • N. Liu, J. Han, D. Zhang, S. Wen, T. Liu, ...
  • DG. Lowe, Distinctive image features from scale-invariant keypoints. International journal ...
  • W. Luo, L. Zhang, Question text classification method of tourism ...
  • S. Murugan, A. Sampathkumar, S. Kanaga Suba Raja, S. Ramesh, ...
  • W. Pitts, WS. McCulloch, How we know universals the perception ...
  • V. Puri, S. Mondal, S. Das, VG. Vrana, Blockchain Propels ...
  • J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You only ...
  • S. Ren, K. He, R. Girshick, J. Sun, Faster r-cnn: ...
  • DE. Rumelhart, GE. Hinton, RJ. Williams, Learning representations by back-propagating ...
  • A. Stuhlsatz, J. Lippel, T. Zielke, Feature extraction with deep ...
  • KK. Sung, T. Poggio, Example-based learning for view-based human face ...
  • FM. Wadley, Probit analysis: a statistical treatment of the sigmoidresponse ...
  • R. Wang, F. Bunyak, G. Seetharaman, K. Palaniappan, Static and ...
  • نمایش کامل مراجع