Design and Development of IOT & AI Enabled Smart Entrance Monitoring Device-Reference-Cited by-同舟云学术

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Design and Development of IOT & AI Enabled Smart Entrance Monitoring Device

Published:2023 Issue: Volume: Page:261-272
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Kundu Krishanu^ORCID,Singh Manas,Singh Aditya Kumar

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-5080-5_23

Reference15 articles.

1. Sujatha R et al (2002) Self-organizing maps and Bayesian regularized neural network for analyzing gasoline and diesel price drifts. Int J Comput Intell Syst 15(1):1–16

2. Navares R et al (2018) Comparing ARIMA and computational intelligence methods to forecast daily hospital admissions due to circulatory and respiratory causes in Madrid. Stochast Environ Res Risk Assess 32(10):2849–2859

3. Cui H et al (2017) Application of minimum relative entropy theory for streamflow forecasting. Stochast Environ Res Risk Assess 31(3):587–608

4. Rahman et al (2020) An automated system to limit COVID-19 using facial mask detection in smart city network. In: 2020 IEEE international IOT, electronics and mechatronics conference (IEMTRONICS). IEEE

5. Meenpal T et al (2019) Facial mask detection using semantic segmentation. In: 2019 4th international conference on computing, communications and security (ICCCS). IEEE, pp 1–5

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. IOT and Machine Learning Based Real-Time Protection Against Cyber-Physical Threat Mitigation;2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2024-05-14

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