To Enhance Object Detection Speed in Meta-Verse Using Image Processing and Deep Learning

Authors

  • Himangi PhD Scholar, Department of Computer Science and Engineering, Baba Mastnath University, Rohtak, Haryana, India
  • Mukesh Singla HOD, Department of Computer Science and Engineering, Faculty of Engineering, Baba Mastnath University, Rohtak, Haryana

Keywords:

Meta-verse, Objective Detection, Image Processing, Deep Learning

Abstract

In the metaverse, people may connect with one another and with digital objects via the use of digital representations created by computers; these representations are called "avatars." The metaverse may also be discovered with the help of an avatar. Envision a world where web-based performance games, virtual reality, and the Internet all come together. In today's world, bitcoin isn't a nice-to-have—it's a need. Cryptocurrency is well equipped to serve as a means of exchange in this rapidly evolving hybrid setting due to its intrinsic decentralised character. Data compression and data security methods are also required. Compression is another area where progress is being made on a regular basis and where new ideas are being developed. While the primary emphasis is on the metaverse, data compression and security are also explored. A new image processing technique, implemented before a DL model is trained and tested, has also helped boost its performance for object detection. The current model's emphasis is on the identification and categorization of meta-verse virtual items. The proposed study has provided a method to enhance the precision of object categorization.

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References

T. Huynh-The, Q. V. Pham, X. Q. Pham, T. T. Nguyen, Z. Han, and D. S. Kim, “Artificial intelligence for the metaverse: A survey,” Eng. Appl. Artif. Intell., vol. 117, no. February, 2023, doi: 10.1016/j.engappai.2022.105581.

R. G. Vallejo, “Metaverse and translation studies : analysis of machine translation Análisis de la traducción automática en los estudios sobre metaverso,” 2023, doi: 10.56294/mr202338.

X. Mu, H. Zhang, J. Shi, J. Hou, J. Ma, and Y. Yang, “Fashion Intelligence in the Metaverse: Promise and Future Prospects,” 2023, [Online]. Available: http://dx.doi.org/10.21203/rs.3.rs-2594075/v1

S. Kaddoura and F. Al Husseiny, “The rising trend of Metaverse in education: challenges, opportunities, and ethical considerations,” PeerJ Comput. Sci., vol. 9, p. e1252, 2023, doi: 10.7717/peerj-cs.1252.

M. Brzeziński and O. I. Poland, “The strategies for innovating with virtual reality and artificial intelligence : a literature review .,” vol. 8, pp. 72–83, 2023.

J. N. Njoku, A. G. Chukwunonso, J. M. Lee, and ..., “Real-time Deep Learning-based Scene Recognition Model For Metaverse Applications,” 한국통신학회 학술대회 …, 2022, [Online]. Available: https://www.researchgate.net/profile/Judith-Njoku-2/publication/358947984_Real-time_Deep_Learning-based_Scene_Recognition_Model_For_Metaverse_Applications/links/621ece137106690c085322b5/Real-time-Deep-Learning-based-Scene-Recognition-Model-For-Metaverse-A

Y. Cho, S. Hong, M. Kim, and J. Kim, “DAVE: Deep Learning-Based Asymmetric Virtual Environment for Immersive Experiential Metaverse Content,” Electron., vol. 11, no. 16, pp. 1–17, 2022, doi: 10.3390/electronics11162604.

S. M. Park and Y. G. Kim, “A Metaverse: Taxonomy, Components, Applications, and Open Challenges,” IEEE Access, vol. 10, pp. 4209–4251, 2022, doi: 10.1109/ACCESS.2021.3140175.

P. M. Singla, “Investigating Role of Deep Learning in Metaverse,” vol. 11, no. 01, pp. 53–60, 2022.

G. Wang et al., “Development of metaverse for intelligent healthcare,” Nat. Mach. Intell., vol. 4, no. 11, pp. 922–929, 2022, doi: 10.1038/s42256-022-00549-6.

A. Naqvi, “A COMPREHENSIVE ANALYSIS OF METAVERSE TECHNOLOGIES TO ATTEMPT A TREND ANALYSIS OF THE EMERGING CONCEPTUAL AND,” no. 15, pp. 23–30, 2022.

N. Ghantous and C. Fakhri, “… Metaverse Through Machine Learning and Blockchain Technology: A Study on Machine Learning, Blockchain, and Their Combination to Enhance Metaverse,” Sci. Prepr., no. July, 2022, doi: 10.14293/S2199-1006.1.SOR-.PP97BSJ.v1.

Y. K. Dwivedi et al., “Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,” Int. J. Inf. Manage., vol. 66, no. July, p. 102542, 2022, doi: 10.1016/j.ijinfomgt.2022.102542.

K. ISRAFILZADE, “Marketing in the Metaverse: A Sceptical Viewpoint of Opportunities and Future Research Directions,” Eurasia Proc. Educ. Soc. Sci., vol. 24, pp. 53–60, 2022, doi: 10.55549/epess.1179349.

Y. Huang and Y. Jin, “Research on the Impact of the Metaverse on the Future of Social Networking,” J. Educ. Humanit. Soc. Sci., vol. 5, pp. 198–204, 2022, doi: 10.54097/ehss.v5i.2902.

K. G. Nalbant and Ş. Uyanık, “Computer Vision in the Metaverse,” J. Metaverse, vol. 1, no. 1, pp. 9–12, 2021.

Swathi, V. N. V. L. S. ., Kumar, G. S. ., & Vathsala, A. V. . (2023). Cloud Service Selection System Approach based on QoS Model: A Systematic Review. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2), 05–13. https://doi.org/10.17762/ijritcc.v11i2.6104

Deshpande, V. (2021). Layered Intrusion Detection System Model for The Attack Detection with The Multi-Class Ensemble Classifier . Machine Learning Applications in Engineering Education and Management, 1(2), 01–06. Retrieved from http://yashikajournals.com/index.php/mlaeem/article/view/10

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Published

12.07.2023

How to Cite

Himangi, & Singla, M. . (2023). To Enhance Object Detection Speed in Meta-Verse Using Image Processing and Deep Learning. International Journal of Intelligent Systems and Applications in Engineering, 11(9s), 176–184. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3106

Issue

Vol. 11 No. 9s (2023)

Section

Research Article

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