Open Access
Issue
Int. J. Simul. Multidisci. Des. Optim.
Volume 15, 2024
Article Number 4
Number of page(s) 9
DOI https://doi.org/10.1051/smdo/2024003
Published online 08 April 2024
  1. E. Bonner, H. Reinders, Augmented and virtual reality in the language classroom: practical ideas, Teach. Engl. Technol. 18, 33–53 (2018) [Google Scholar]
  2. T. Polić, E. Krelja Kurelović, Corpus-based vocabulary learning in technical English, Int. J. Comput. Linguist. 12, 35–55 (2021) [Google Scholar]
  3. L. Hongyan, A study on corpus-based EFL vocabulary teaching, ISLLAC: J. Intensive Stud. Lang. Liter. Art Culture 2, 21–25 (2018) [CrossRef] [Google Scholar]
  4. L. Yang, A. Coxhead, A corpus-based study of vocabulary in the new concept English textbook series, RELC J. 53, 597–611 (2022) [CrossRef] [Google Scholar]
  5. H. Lee, M. Warschauer, J.H. Lee, Toward the establishment of a data‐driven learning model: role of learner factors in corpus‐based second language vocabulary learning, Mod. Lang. J. 104, 345–362 (2020) [CrossRef] [Google Scholar]
  6. R. Gholaminejad, M.R.A. Sarab, Academic vocabulary and collocations used in language teaching and applied linguistics textbooks: a corpus-based approach, Terminology 26, 82–107 (2020) [Google Scholar]
  7. L. Lowphansirikul, C. Polpanumas, A.T. Rutherford, S. Nutanong, A large English-Thai parallel corpus from the web and machine-generated text, Lang. Resour. Eval. 56, 477–499 (2022) [CrossRef] [Google Scholar]
  8. J. Kirk, G. Nelson, The International Corpus of English project: a progress report, World Englishes 37, 697–716 (2018) [CrossRef] [Google Scholar]
  9. P. Crosthwaite, L.L.C. Wong, J. Cheung, Characterising postgraduate students' corpus query and usage patterns for disciplinary data-driven learning, ReCALL 31, 255–275 (2019) [CrossRef] [Google Scholar]
  10. H.C. Yeh, S.S. Tseng, L. Heng, Enhancing EFL students' intracultural learning through virtual reality, Interact. Learn. Environ. 30, 1609–1618 (2022) [CrossRef] [Google Scholar]
  11. J. Cui, Application of deep learning and target visual detection in English vocabulary online teaching, J. Intell. Fuzzy Syst. 39, 5535–5545 (2020) [CrossRef] [Google Scholar]
  12. F. El Jamiy, R. Marsh, Survey on depth perception in head mounted displays: distance estimation in virtual reality, augmented reality, and mixed reality, IET Image Process. 13, 707–712 (2019) [CrossRef] [Google Scholar]
  13. M. Liao, J. Zhang, Z. Wan, F. Xie, J. Liang, P. Lyu, X. Bai, Scene text recognition from two-dimensional perspective, Proc. AAAI Conf. Artif. Intell. 33, 8714–8721 (2019) [Google Scholar]
  14. Y. Xu, Y. Wang, W. Zhou, Y. Wang, Z. Yang, X Bai, Textfield: learning a deep direction field for irregular scene text detection,IEEE Trans. Image Process. 28, 5566–5579 (2019) [CrossRef] [MathSciNet] [Google Scholar]
  15. T. Wang, Y. Zhu, L. Jin, C. Luo, X. Chen, Y. Wu, M. Cai, Decoupled attention network for text recognition, Proc. AAAI Conf. Artif. Intell. 34, 12216–12224 (2020) [Google Scholar]
  16. B. Yildirim, E.S. Topalcengiz, G. Arikan, S. Timur, Using virtual reality in the classroom: reflections of STEM teachers on the use of teaching and learning tools, J. Educ. Sci. Environ. Health 6, 231–245 (2020) [Google Scholar]
  17. C. Norberg, M. Nordlund, A corpus-based study of lexis in L2 English textbooks, J. Lang. Teach. Res, 9, 463–473 (2018) [CrossRef] [Google Scholar]
  18. M. Siddiq, L.M.Q. Arif, S.C. Shafi, A survey research analysis of effectiveness of vocabulary learning through English vocabulary corpus, Int. J. Educ. Pedagogy 3, 1–13 (2021) [Google Scholar]
  19. R. Dhaya, Improved image processing techniques for user immersion problem alleviation in virtual reality environments, J. Innov. Image Process. 2, 77–84 (2020) [CrossRef] [Google Scholar]
  20. S. Long, X. He, C. Yao, Scene text detection and recognition: the deep learning era, Int. J. Comput. Vis. 129, 161–184 (2021) [CrossRef] [Google Scholar]
  21. Y. Meng, J. Shen, C. Zhang, Weakly-supervised hierarchical text classification, Proc. AAAI Conf. Artif. Intell. 33, 6826–6833 (2019) [Google Scholar]
  22. D.S. Sachan, M. Zaheer, R. Salakhutdinov, Revisiting lstm networks for semi-supervised text classification via mixed objective function, Proc. AAAI Conf. Artif. Intell. 33, 6940–6948 (2019) [Google Scholar]
  23. S. Minaee, N. Kalchbrenner, E. Cambria et al., Deep learning-based text classification: a comprehensive review, ACM Comput. Surv. 54, 1–40 (2021) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.