Open Access
| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01055 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001055 | |
| Published online | 06 October 2023 | |
- S. Ahmed, H. Wang, and Y. Tian, “Adaptive high-order terminal sliding mode control based on time delay estimation for the robotic manipulators with backlash hysteresis,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 2, pp. 1128–1137, (2021). View at: Publisher Site | Google Scholar [CrossRef] [Google Scholar]
- J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You only look once: unified, real-time object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779–788, Las Vegas, NV, USA, June (2016). View at: Google Scholar [Google Scholar]
- A. Farhadi and R. Joseph, CVPR, (2018). View at: Google Scholar [Google Scholar]
- M. Grega, A. Matiolański, P. Guzik, and M. Leszczuk, NIH Sensors, vol. 16, no. 1, p. 47, (2016). View at: Publisher Site | Google Scholar [CrossRef] [Google Scholar]
- L. Pang, H. Liu, Y. Chen, and J. Miao, “MDPI,” Sensors, vol. 20, no. 6, p. 1678, (2020) View at: Publisher Site | Google Scholar [CrossRef] [PubMed] [Google Scholar]
- Warsi, M. Abdullah, M. N. Husen, M. Yahya, S. Khan, and N. Jawaid, “Gun detection system using YOLOv3,” in Proceedings of the 2019 IEEE International Conference on Smart Instrumentation, Measurement and Application (ICSIMA), pp. 1–4, IEEE, Kuala Lumpur, Malaysia, August (2019). View at: Google Scholar [Google Scholar]
- G. K. Verma and A. Dhillon, “A handheld gun detection using faster r-cnn deep learning,” in Proceedings of the 7th International Conference on Computer and Communication Technology, pp. 84–88, Kurukshetra, Haryana, November (2017). View at: Google Scholar. [Google Scholar]
- P. C. S. Reddy, S. G. Rao, G. R. Sakthidharan and P. V. Rao, Age Grouping with Central Local Binary Pattern based Structure Co-occurrence Features, In International Conference on Smart Systems and Inventive Technology (ICSSIT), (2018) [Google Scholar]
- Gundavarapu, M.R., Saginala, R., Varma, M.A., ... Bodduluri, A.S., Moparthy, L.C. Deep Learning Framework for Liver CT Image Segmentation and Risk Prediction in Conference, Lecture Notes in Networks and Systemsthis link is disabled, 2023, 645 LNNS, pp. 189–201. [Google Scholar]
- Chandra Sekhar Reddy P, Sakthidharan G, Kanimozhi Suguna S, Mannar Mannan J, Varaprasada Rao P, International Journal of Engineering and Advanced Technology. 8, (2019) [Google Scholar]
- P. Chandra Sekhar Reddy, B. Eswara Reddy and V. Vijaya Kumar, International Journal of Image, Graphics and Signal Processing. 4, (2012) [Google Scholar]
- Somasekar, J Ramesh, G “Beneficial Image Preprocessing by Contrast Enhancement Technique for SEM Images”, IJEMS Vol.29(6) December 2022, NIScPR-CSIR,India. [Google Scholar]
- P. C. S. Reddy, S. G. Rao, G. R. Sakthidharan and P. V. Rao, Age Grouping with Central Local Binary Pattern based Structure Co-occurrence Features, In International Conference on Smart Systems and Inventive Technology (ICSSIT), (2018) [Google Scholar]
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