Monitoring Employees Entering and Leaving the Office with Deep Learning Algorithms-Reference-Cited by-同舟云学术

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Monitoring Employees Entering and Leaving the Office with Deep Learning Algorithms

Published:2022 Issue: Volume: Page:641-658
ISSN:2367-4512
Container-title:Artificial Intelligence in Data and Big Data Processing
language:
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Author:

Hoang Viet Tran,Minh Khoi Tran,Hieu Nghia Dang,Hoang Viet Nguyen

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-97610-1_51

Reference17 articles.

1. Sawhney S, Kacker K, Jain S, Singh SN, Garg R (2019) Real-time smart attendance system using face recognition techniques. In: 2019 9th ınternational conference on cloud computing, data science and engineering (Confluence), pp 522–525. https://doi.org/10.1109/CONFLUENCE.2019.8776934

2. Arachchilage SW, Izquierdo E (2019) A framework for real-time face-recognition. In: 2019 IEEE visual communications and ımage processing (VCIP), pp 1–4. https://doi.org/10.1109/VCIP47243.2019.8965805

3. Khan M, Chakraborty S, Astya R, Khepra S (2019) Face detection and recognition using openCV. In: 2019 ınternational conference on computing, communication, and ıntelligent systems (ICCCIS), pp 116–119. https://doi.org/10.1109/ICCCIS48478.2019.8974493

4. Zhang K, Zhang Z, Li Z, Qiao Y (2016) Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process Lett 23(10):1499–1503. https://doi.org/10.1109/LSP.2016.2603342,Oct

5. Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vision 57(2):137–154. https://doi.org/10.1023/B:VISI.0000013087.49260.fb

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