Real-time eye state recognition using dual convolutional neural network ensemble-Reference-Cited by-同舟云学术

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Real-time eye state recognition using dual convolutional neural network ensemble

Published:2022-03-16 Issue:3 Volume:19 Page:607-622
ISSN:1861-8200
Container-title:Journal of Real-Time Image Processing
language:en
Short-container-title:J Real-Time Image Proc

Author:

Saurav Sumeet^ORCID,Gidde Prashant,Saini Ravi,Singh Sanjay

Publisher

Springer Science and Business Media LLC

Subject

Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s11554-022-01211-5.pdf

Reference46 articles.

1. Zhao, L., Wang, Z., Zhang, G., Qi, Y., Wang, X.: Eye state recognition based on deep integrated neural network and transfer learning. Multimed. Tools Appl. 77(15), 19415–19438 (2018)

2. Liu, A., Li, Z., Wang, L., Zhao, Y.: A practical driver fatigue detection algorithm based on eye state. In: 2010 Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia), IEEE, pp 235–238 (2010)

3. Królak, A., Strumiłło, P.: Eye-blink detection system for human-computer interaction. Univ. Access Inf. Soc. 11(4), 409–419 (2012)

4. Fuangkaew, S., Patanukhom, K.: Eye state detection and eye sequence classification for paralyzed patient interaction. In: 2013 2nd IAPR Asian Conference on Pattern Recognition, IEEE, pp 376–380 (2013)

5. Liu, Z. T., Jiang, C.S., Li, S.H., Wu, M., Cao, W.H., Hao, M.: Eye state detection based on weight binarization convolution neural network and transfer learning. Applied Soft Computing, p 107565 (2021)

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3. Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review;Multimedia Tools and Applications;2023-06-19

4. Camera based Eye State Estimation for ICU Patients: A Pilot Clinical Study;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

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