EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 92 (2021) SHS Web of Conf., 92 (2021) 06034 References
Open Access
Issue
SHS Web of Conf.
Volume 92, 2021
The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
Article Number 06034
Number of page(s) 10
Section Corporate Social Responsibility and Consumer Claims
DOI https://doi.org/10.1051/shsconf/20219206034
Published online 13 January 2021
  1. Cheng, M.M., Liu, X.C., Wang, J., Lu, S.P., Lai, Y.K., Rosin, P.L. (2019). Structure-Preserving Neural Style Transfer. IEEE Transactions on Image Processing (TIP), 29, 909–920. [Google Scholar]
  2. Ardic, O.P., Heimann, M., Mylenko, N. (2011). Access to Financial Services and the Financial Inclusion Agenda around the World. A Cross-Country Analysis with a New Data Set. The World Bank. [Google Scholar]
  3. Game, A. (2001). Creative ways of being. In J. R. Morss, N. Stephenson & J. F. H. V. Rappard (Eds.). Theoretical issues in psychology: Proceedings of the International Society for Theoretical Psychology 1999 Conference (pp. 3-12). Sydney: Springer. [Google Scholar]
  4. Marinescu, D.C., Marinescu, G.M. (2012). Classical and Quantum Information Theory, in Classical and Quantum Information. Elsevier, 4, 212-344. [Google Scholar]
  5. Goodfellow, I., Bengio, Y., Courville, A. (2016). Deep Learning, Deep Learning: adaptive computation and machine learning. The MIT Press. [Google Scholar]
  6. Babus, A., Allen, F. (2011). Networks in Finance. Wharton Financial Institutions Center Working Paper, 8, 1-20. [Google Scholar]
  7. Mobarek, A., Al-Ammary, J. H., Ezeoha, A., Sahut, J-M., Hosseini, M. H., Ghorbani, A. (2011). The E-Banking Strategies. Section 2. E-Banking and Emerging Multidisciplinary Processes. IGI Global. [Google Scholar]
  8. Baruah, T.D. (2012). Effectiveness of Social Media as a tool of communication and its potential for technology enabled connections: A micro-level study. International Journal of Scientific and Research Publications, 2(5), 1-10. [Google Scholar]
  9. Luo, C., Lin, Q., Liu, Y., Jin, L., Shen, C. (2020). Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild. Cornell University. [Google Scholar]
  10. Fang, S., Xie, H., Chen, J., Tan, J., Zhang, Y. (2019). Learning to Draw Text in Natural Images with Conditional Adversarial Networks: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) (pp. 715-722). Macao: Springer. [Google Scholar]
  11. Cozby, P., Bates, S. (2017). Methods in Behavior Research. McGraw-Hill. [Google Scholar]
  12. Hellman, Z., Peretz, R. (2020). A Survey on Entropy and Economic Behaviour. Entropy, 22(2), 157-168. [CrossRef] [Google Scholar]
  13. Ramiro, H., Gálvez, R. H., Gravano, A. (2017). Assessing the usefulness of online message board mining in automatic stock prediction systems. Journal of Computational Science, 19, 1877-7503. [Google Scholar]
  14. Wasserman, S., Faust, K. (1994). Social network analyses: Methods and applications. 1st Edition. Cambridge: Cambridge University Press. [CrossRef] [Google Scholar]
  15. Chen, X., Li, S., Li, H., Jiang, S., Song, L. (2019). Generative Adversarial User Model for Reinforcement Learning Based Recommendation System: Proceedings of the 36th International Conference on Machine Learning (ICML 2019) (pp. 1052-1061). California: Springer. [Google Scholar]
  16. Hanafizadeh, P., Ravasan, A. Z., Nabavi, A., Mehrabioun, M. (2012). A Literature on the Business Impact of Social Network Sites. International Journal of Virtual Communities and Social Networking, 4 (1),1-15. [CrossRef] [Google Scholar]
  17. Salton, G., McGill, M. J. (1983). Introduction to Modern Information Retrieval. McGraw-Hill Book Co.: New York. [Google Scholar]
  18. Gandomi, A., Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144. [CrossRef] [Google Scholar]
  19. Boehmle, B., Greenwell, B. M. (2019). Hands-On Machine Learning. R. Taylor & Francis Group. [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.