DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2020/11/06
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Journal
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Indian UGC (journal)
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Refrences36
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Citations15
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Taeseok Kang
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Minsu Chae
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Eunbin Seo
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Mingyu Kim
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Jinmo Kim ORCID (unauthenticated)
Abstract
Cite
Kang, Taeseok, et al. “DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality”. Electronics, vol. 9, no. 11, 2020, p. 1863, https://doi.org/10.3390/electronics9111863.
Kang, T., Chae, M., Seo, E., Kim, M., & Kim, J. (2020). DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality. Electronics, 9(11), 1863. https://doi.org/10.3390/electronics9111863
Kang, Taeseok, Minsu Chae, Eunbin Seo, Mingyu Kim, and Jinmo Kim. “DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality”. Electronics 9, no. 11 (2020): 1863. https://doi.org/10.3390/electronics9111863.
Kang T, Chae M, Seo E, Kim M, Kim J. DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality. Electronics. 2020;9(11):1863.
Journal Categories
Science
Physics
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Engineering (General)
Civil engineering (General)
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Transcending the Self in Immersive Virtual Reality | Computer |
| 2014 | |
| Measuring Usability with the USE Questionnaire | 2001 | |||
MAVE: Maze‐based immersive virtual environment for new presence and experience | Computer Animation and Virtual Worlds |
| 25 | 2017 |
| 10.1109/TBME.2007.908087 | ||||
The Factor Structure of the Presence Questionnaire | Presence: Teleoperators and Virtual Environments |
| 333 | 2005 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| ASL champ!: a virtual reality game with deep-learning driven sign recognition | Computers & Education: X Reality | 2024 | ||
| Real-time hand interaction and self-directed machine learning agents in immersive learning environments | Computers & Education: X Reality | 1 | 2023 | |
| Application of Virtual Avatar using Motion Capture in Immersive Virtual Environment | International Journal of Human–Computer Interaction |
| 2 | 2023 |
| XAVE: Cross-Platform Based Asymmetric Virtual Environment for Immersive Content | IEEE Access |
| 2023 | |
Machine learning-based cognitive load prediction model for AR-HUD to improve OSH of professional drivers | Frontiers in Public Health |
| 2023 |
Citations Analysis
The category
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks 6
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Improving Classification Accuracy of Hand Gesture Recognition Based on 60 GHz FMCW Radar with Deep Learning Domain Adaptation and was published in 2020. The most recent citation comes from a 2024 study titled ASL champ!: a virtual reality game with deep-learning driven sign recognition. This article reached its peak citation in 2021, with 6 citations. It has been cited in 10 different journals, 40% of which are open access. Among related journals, the Electronics cited this research the most, with 4 citations. The chart below illustrates the annual citation trends for this article.