Open Access
| Issue |
E3S Web Conf.
Volume 684, 2026
International Conference on Engineering for a Sustainable World (ICESW 2025)
|
|
|---|---|---|
| Article Number | 03005 | |
| Number of page(s) | 12 | |
| Section | Engineering Innovation and Social Environment | |
| DOI | https://doi.org/10.1051/e3sconf/202668403005 | |
| Published online | 07 January 2026 | |
- C. Canuto, J. Leonid, A. Samatelo, and R. F. Vassallo, "Neurocomputing Dynamic gesture recognition by using CNNs and star RGB : A temporal information condensation," Neurocomputing, vol. 400, pp. 238–254, 2020, doi: 10.1016/j.neucom.2020.03.038. [Google Scholar]
- X. Chen, "Hand and gesture," vol. 3, no. 3, 2021, doi: 10.1016/S2096-5796(21)00049-8. [Google Scholar]
- M. Al-hammadi, G. Muhammad, and W. Abdul, "Hand Gesture Recognition Using 3D-CNN Model," IEEE Consum. Electron. Mag., vol. 9, no. February 2020, pp. 95–101, 2020, doi: 10.1109/MCE.2019.2941464. [Google Scholar]
- Y. Wang, S. Wang, M. Zhou, Q. Jiang and Z. Tian, "TS-I3D Based Hand Gesture Recognition Method With Radar Sensor," in IEEE Access, vol. 7, pp. 22902–22913, 2019, doi: 10.1109/ACCESS.2019.2897060. [Google Scholar]
- D. K. Singh, "ScienceDirect 3D-CNN based based Dynamic Dynamic Gesture Gesture Recognition Recognition for for Indian Indian Sign Sign Language Language Modeling Modeling," Procedia Comput. Sci., vol. 189, pp. 76–83, 2021, doi: 10.1016/j.procs.202L05.071. [Google Scholar]
- F. Noble, M. Xu, F. Alam, Static Hand Gesture Recognition Using Capacitive Sensing and Machine Learning. Sensors, 23, 3419, 2023, doi: 10.3390/s23073419. [Google Scholar]
- J. Yu, M. Qin, S. Zhou, Dynamic gesture recognition based on 2D convolutional neural network and feature fusion. Sci Rep 12, 4345, 2022, doi: 10.1038/s41598-022-08133-z. [Google Scholar]
- Q. Guo, M. Ren, S. Wu, and Y. Sun, "Applications of artificial intelligence in the field of air pollution : A bibliometric analysis," 2022. [Google Scholar]
- W. Wang, M. He, X. Wang, J. Ma, H. Song, Medical Gesture Recognition Method Based on Improved Lightweight Network. Appl. Sci, 12, 6414, 2022, doi: 10.3390/app12136414. [Google Scholar]
- M. M. H. Noor Adnan Ibraheem and R. Khan, "An Investigation on Gesture Analysis and Geometric Features Extraction," no. February, 2015, doi: 10.15680/ijircce.2015.0301037. [Google Scholar]
- M. Oudah, A. Al-naji, and J. Chahl, "Hand Gesture Recognition Based on Computer Vision : A Review of Techniques," 2020. [Google Scholar]
- R. Azad, M. Asadi-Aghbolaghi, S. Kasaei and S. Escalera, "Dynamic 3D Hand Gesture Recognition by Learning Weighted Depth Motion Maps," in IEEE Trans. on Cir. and Sys. for Video Tech., vol. 29, no. 6, pp. 1729–1740, June 2019, doi: 10.1109/TCSVT.2018.2855416. [Google Scholar]
- R. Patel and S. Patel, "A Comprehensive Study of Applying Convolutional Neural Network for Computer Vision," vol. 29, no. 6, pp. 2161-2174, 2020. [Google Scholar]
- N. Yu and J. Lv, "Human body posture recognition algorithm for still images," vol. 2020, no. Acait 2019, pp. 322–325, 2020, doi: 10.1049/joe.2019.1146. [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.