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All issues Volume 391 (2023) E3S Web Conf., 391 (2023) 01182 References
Open Access
Issue
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
Article Number 01182
Number of page(s) 8
DOI https://doi.org/10.1051/e3sconf/202339101182
Published online 05 June 2023
  1. X. Zhao, S. Zhang, “A review on facial expression recognition: feature extraction and classification”, IETE Tech. Rev., 33 (2016), pp. 505–517, 10.1080/02564602.2015.1117403. [CrossRef] [Google Scholar]
  2. Caifeng Shan, Shaogang Gong and Peter W. McOwan, “Robust Facial Expression Recognition Using Local Binary Patterns” 0-7803-9134- 9/05/$20.00 (2005), IEEE. [Google Scholar]
  3. Karthik Rao, R., Bobba, P.B., Suresh Kumar, T., Kosaraju, S., Feasibility analysis of different conducting and insulation materials used in laminated busbars, Materials Today: Proceedings, 2019, 26, pp. 3085–3089. [Google Scholar]
  4. S.L. Happy1, Anjith George2, Aurobinda Routray3, “A Real Time Facial Expression Classification System Using Local Binary Patterns”, IEEE Proceedings, Kharagpur, India, December 27-29, (2012) [Google Scholar]
  5. Hua Gao, Anil Yuce, Jean-Philippe Thiran, “Detecting Emotional Stress From Facial Expressions For Driving Safety”, 978-1-4799-5751- 4/14/$31.00 (2014) IEEE. [Google Scholar]
  6. Tummala, S.K., Indira Priyadarshini, T., Morphological Operations and Histogram Analysis of SEM Images using Python, Indian Journal of Engineering and Materials Sciences, 2022, 29(6), pp. 794–798. [Google Scholar]
  7. Muzammil Abdulrahman, Alaa Eleyan ,“Facial Expression Recognition Using Support Vector Machines,” 978-1-4799-4874-1/14/$31.00,(2015), IEEE. [Google Scholar]
  8. Christopher Pramerdorfer, Martin Kampel,” Facial Expression Recognition using Convolutional Neural Networks: State of the Art”, arXiv:1612.02903v1, [cs.CV] 9 December (2016). [Google Scholar]
  9. Suresh Kumar Tummala, Phaneendra Babu Bobba & Kosaraju Satyanarayana (2022) SEM & EDAX analysis of super capacitor, Advances in Materials and Processing Technologies, 8:sup 4, 2398–2409, [CrossRef] [Google Scholar]
  10. Aditi Bhadane1, Anuja Dixit2, Vivek Ingle3, Disha Shastri4, “Facial Expression Recognition Using Image Processing”, IJARIIE-ISSN(O)- 2395-4396, Vol-5 Issue-3,(2019). [Google Scholar]
  11. Huijun Zhang, Ling Feng, Ningyun Li, Zhanyu Jin and Lei Cao, “Video-Based Stress Detection through Deep Learning” Sensors (2020), Vol-20, 5552; DOI: 10.3390/s20195552. [CrossRef] [PubMed] [Google Scholar]
  12. Seyed Muhammad Hossein Mousavi1 · S. Younes Mirinezhad1, “Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor”, SN Applied Sciences (2021) 3:19 — https://doi.org/10.1007/s42452-020-03999-y. [CrossRef] [Google Scholar]
  13. Davu, S.R., Tejavathu, R. & Tummala, S.K. EDAX analysis of poly crystalline solar cell with silicon nitride coating. Int J Interact Des Manuf (2022). [Google Scholar]
  14. Viola P., and Michael J. (2001), “Rapid object detection using a boosted cascade of simple features.”, Computer Vision and Pattern Recognition, (2001), IEEE Computer Society Conference on. Vol. 1. IEEE. [Google Scholar]
  15. Mousavi SMH (2018) ,“A new way to age estimation for rgbd images, based on a new face detection and extraction method for depth images”, Int. J Image Gr. Signal Process 10(11):10. [Google Scholar]
  16. William F.T., and Michal R. (1995), “Orientation histograms for hand gesture recognition.” International workshop on automatic face and gesture recognition. Vol. 12. [Google Scholar]
  17. Cortes C., Vapnik V. (1995) Support-vector networks. Mach Learn 20(3):273–297. [Google Scholar]
  18. J. Srinivas Rao, Suresh Kumar Tummala, Narasimha Raju Kuthuri, Comparative investigation of 15 Level and 17 level cascaded h-bridge MLI with cross h-bridge MLI fed permanent magnet synchronous motor, Indonesian Journal of Electrical Engineering and Computer Science, 21(2), pp: 723–734, (2020) [Google Scholar]
  19. Nielsen M.A. (2015) Neural networks and deep learning, vol 25. Determination press, San Francisco [Google Scholar]
  20. Mohammad Failzal1, Nikhil V.3, Prajwal C.4, Aruna Rao B.P.,“Recognition of Stress Using Face Image and Facial Landmarks”, International Advanced Research Journal in Science, Engineering and Technology, Vol. 8, Issue 5, May 2021. [Google Scholar]
  21. Tummala, S.K., Kosaraju, S. & Bobba, P.B. Optimized power generation in solar using carbon substrate for reduced greenhouse gas effect. Appl Nanosci 12, 1537–1543 (2022). [CrossRef] [Google Scholar]
  22. Swapna Subudhiray, Hemanta Kumar Palo, Niva Das, ”K-nearest neighbor based facial emotion recognition using effective features”, IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 12, No. 1, March (2023), pp. 57–65 ISSN: 2252-8938, DOI: 10.11591/ijai.v12.i1.pp57-65. [CrossRef] [Google Scholar]
  23. Lakshmi and R. Ponnusamy, “Facial emotion recognition using modified HOG and LBP features with deep stacked auto encoders,” Microprocessors and Microsystems, vol. 82, 2021, DOI: 10.1016/j.micpro.(2021).103834. [CrossRef] [Google Scholar]
  24. Satyanarayana Kosaraju, Swadesh Kumar Singh, Tanya Buddi, Anil Kalluri & Ahsan Ul Haq (2020) Evaluation and characterisation of ASS316L at sub-zero temperature, Advances in Materials and Processing Technologies, 6:2, 365–375 [CrossRef] [Google Scholar]
  25. Y. Tong and R. Chen, “Local Dominant Directional Symmetrical Coding Patterns for Facial Expression Recognition,” Computational Intelligence and Neuroscience, vol. 1, (2019), DOI: 10.1155/2019/3587036. [Google Scholar]
  26. Satyanarayana, K., Gopal, A.V., Babu, P.B., Design optimisation of machining parameters for turning titanium alloys with taguchi-grey method, International Journal of Machining and Machinability of Materials, 2013, 13(2-3), pp. 191–202 [CrossRef] [Google Scholar]
  27. Z. Xiang, H. Tan, and W. Ye, “The Excellent Properties of a Dense Grid-Based HOG Feature on Face Recognition Compared to Gabor and LBP,” IEEE Access, vol. 6, pp. 29306–29318, (2018), DOI: 10.1109/AC-CESS.2018.2813395. [CrossRef] [Google Scholar]
  28. Nagarjuna, A., Suresh Kumar, T., Yogeswara Reddy, B., Udaykiran, M., Fifteen level cascaded H-bridge multilevel inverter fed induction motor, International Journal of Innovative Technology and Exploring Engineering, 2019, 8(11), pp. 640–645. [CrossRef] [Google Scholar]
  29. H. K. Meena, S. D. Joshi, and K. K. Sharma, “Facial Expression Recognition Using Graph Signal Processing on HOG,” IETE Journal of Research, vol. 67, no. 5, pp. 667–673, (2021), DOI: 10.1080/03772063.2019.1565952. [CrossRef] [Google Scholar]
  30. Raju, N.A., Suresh Kumar, T., Forward converter based switch mode power supply with modified boost converter as PFC, International Journal of Innovative Technology and Exploring Engineering, 2019, 8(11), pp. 3860–3864 [CrossRef] [Google Scholar]

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