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All issues Volume 430 (2023) E3S Web Conf., 430 (2023) 01067 References
Open Access
Issue
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
Article Number 01067
Number of page(s) 10
DOI https://doi.org/10.1051/e3sconf/202343001067
Published online 06 October 2023
  1. M. S. A. Vigil, M. Mirutuhula, S. Sarvagna, R. Supraja, and G. P. Reddy, “DNA Sequencing Using Machine Learning Algorithms,” in 2022 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI), Chennai, India, (2022), pp. 1-4, doi: 10.1109/ICDSAAI55433.2022.10028805. [Google Scholar]
  2. Yang, Aimin, et al. Yang A, Zhang W, Wang J, Yang K, Han Y, Zhang L. “ NIH 8 (2020): 1032. [Google Scholar]
  3. S. W. Davies, M. Eizenman, and S. Pasupathy, in IEEE TBME, 46, no. 9, pp. 1044-K1056, Sept. (1999), doi: 10.1109/10.784135. [Google Scholar]
  4. F. han, C. Ncube, L. K. Ramasamy, S. Kadry, and Y. Nam,in IEEE Access, 8, pp. 119710-119719, (2020), doi: 10.1109/ACCESS.2020.3003785. [CrossRef] [Google Scholar]
  5. Bonat, Ernest, Ph D. Bishes, and M. S. Rayamajhi, in IEEE Access, 8,Digital Object Identifier 10.1109/ACCESS.2020.3003785 [Google Scholar]
  6. Bonev, B., Cavalli, G. NIH 17, 11 (2016): 661-678. doi:10.1038/nrg.2016.112 [Google Scholar]
  7. Branco, M.R. & Pombo, A. NIH 4,5 (2006): e138. doi:10.1371/journal.pbio.0040138 [Google Scholar]
  8. Su, J. H., Zheng, P., Kinrot, S. S., Bintu, B. & Zhuang, X. NIH 182, 6 (2020): 1641-1659.e26. doi:10.1016/j.cell.2020.07.032 [Google Scholar]
  9. Su, Jun-Han, et al. NIH 182, 6 (2020): 1641-1659.e26. doi:10.1016/j.cell.2020.07.032 [Google Scholar]
  10. Fudenberg, Geoffrey, et al. MIT Libraries 82. Cold Spring Harbor Laboratory Press, (2017). [Google Scholar]
  11. Rao, Suhas SP, et al. NIH 159, 7 (2014): 1665-80. doi:10.1016/j.cell.2014.11.021 [Google Scholar]
  12. Guo, Ya, et al. NIH 162, 4 (2015): 900-10. doi:10.1016/j.cell.2015.07.038 [Google Scholar]
  13. Reddy, N.M., Ramesh, G., Kasturi, S.B. et al. NIH 162, 4 (2015): 712-25. doi:10.1016/j.cell.2015.07.046 [Google Scholar]
  14. G. Ramesh, Avinash Sharma, D. V. Lalitha Parameswari, Ch. Mallikarjuna Rao & J. Somasekar JDMSC(2022) 25: 4, 891-901, DOI: 10.1080/09720529.2022.2068598 [Google Scholar]
  15. Ramesh, G., Reddy, K.S.S., Ramu, G., Reddy, Y.C.A.P., Somasekar, J. (2023). An Empirical Study on Discovering Software Bugs Using Machine Learning Techniques. In: Buyya, R., Hernandez, S.M., Kovvur, R.M.R., Sarma, T.H. (eds) Computational Intelligence and Data Analytics. Lecture Notes on Data Engineering and Communications Technologies, 142. Springer, Singapore. https://doi.org/10.1007/978-981-19-3391-2_14 [Google Scholar]
  16. Dhanke Jyoti Atul et al. (2021) Microprocessors and Microsystems, 82, 103741. (Elsevier) [CrossRef] [Google Scholar]
  17. G. Ramesh et al., IJRTE, ISSN: 2277-3878, 8, Issue-1, May 2019. [Google Scholar]
  18. Ramesh, G., Anugu, A., Madhavi, K., Surekha, P. (2021). “Automated Identification and Classification of Blur Images, Duplicate Images Using Open CV. In: Luhach, A.K., Jat, D.S., Bin Ghazali, K.H., Gao, XZ, Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2020. Communications in Computer and Information Science, 1393. Springer, Singapore. https://doi.org/10.1007/978-981-16-3660-8_52 [Google Scholar]
  19. Kumar, S.K., Reddy, P.D.K., Ramesh, G., Maddumala, V.R. (2019). Traitement du Signal, 36, No. 3, pp. 233-237. https://doi.org/10.18280/ts.360305 [Google Scholar]
  20. Parameswari, D.V.L., Rao, C.M., Kalyani, D. et al. Appl Nanosci (2021). https://doi.org/10.1007/s13204-021-01969-3 [Google Scholar]
  21. G. Ramesh, J. Praveen, “Artificial Intelligence (AI) Framework for Multi-Modal Learning and Decision Making towards Autonomous and Electric Vehicles”, E3S Web Conf. 309 01167 (2021), DOI: 10.1051/e3sconf/202130901167 [CrossRef] [EDP Sciences] [Google Scholar]
  22. Y. Sara, J. Dumne, A. Reddy Musku, D. Devarapaga, and R. Gajula, “A Deep Learning Facial Expression Recognition based Scoring System for Restaurants,” in 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, (2022), pp. 630-634. [Google Scholar]
  23. Chandrika Lingala, and Karanam Madhavi et.al, “A Survey on Cardivascular Prediction using Variant Machine learning Solutions.” E3S Web of Conferences 309, 01042 (2021), https://doi.org/10.1051/e3sconf/202130901042. [CrossRef] [EDP Sciences] [Google Scholar]
  24. Chandrika Lingala, and Karanam Madhavi, “A Hybrid Framework for Heart Disease Prediction Using Machine Learning Algorithms”, E3S Web of Conferences 309, 01043 (2021). https://doi.org/10.1051/e3sconf/202130901043 [CrossRef] [EDP Sciences] [Google Scholar]

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