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Recent publications

1. Sudeepa, K., Aithal, G., Rajinikanth, V., & Satapathy, S. (2020). Genetic algorithm based key sequence generation for cipher system. Pattern Recognition Letters, 133, 341-348. https://doi.org/10.1016/j.patrec.2020.03.015

2. Dewangan, B., Agarwal, A., Choudhury, T., Pasricha, A., & Chandra Satapathy, S. (2020). Extensive review of cloud resource management techniques in industry 4.0: Issue and challenges. Software: Practice And Experience. https://doi.org/10.1002/spe.2810

3. Arshad, H., Khan, M. A., Sharif, M. I., Yasmin, M., Tavares, J. M., Zhang, Y., & Satapathy, S. C. (2020). A multilevel paradigm for deep convolutional neural network features selection with an application to human gait recognition. Expert Systems. https://doi.org/10.1111/exsy.12541

4. Bhattacharjee, K., Pant, M., Zhang, Y., & Satapathy, S. (2020). Multiple Instance Learning with Genetic Pooling for medical data analysis. Pattern Recognition Letters, 133, 247-255. https://doi.org/10.1016/j.patrec.2020.02.025

5. Goswami, D. k., Bilgaiyan, S., & Mishra, S. (2020). Effort estimation of web based projects: a systematic review. International Journal of Productivity and
Quality Management, Inderscience, 2678–2682 (Accepted & In Press).

6. Aditya, Shrivastava, A., & Bilgaiyan, S. (2020). Abstractive text summarization and unsupervised text classifier. In Machine learning and information processing, icmlip, springer(pp. 355–365). Springer, Singapore. doi:10.1007/978-981-15-1884-3_33

7. 2Sinha, S., Mishra, S. K., & Bilgaiyan, S. (2020). Emotion analysis to provide counseling to students fighting from depression and anxiety by using cctv
surveillance. In Machine learning and information processing, icmlip, springer (pp. 81–94). Springer, Singapore. doi:10.1007/978-981-15-1884-3_8

8. Bilgaiyan, S., Panigrahi, P. K., & Mishra, S. (2020). Chaos-based modified morphological genetic algorithm for effort estimation in agile software
development. A Journey Towards Bio-inspired Techniques in Software Engineering, (pp. 89-102), Springer

9. Reddy, A.V.N., Krishna, C.P. & Mallick, P.K.(2020) An image classification framework exploring the capabilities of extreme learning machines and artificial bee colony. Neural Comput & Applic 32, 3079–3099 .(SCIE and SCOPUS)

10. Rohit Halder, Rajdeep Chatterjee, Debarshi Kumar Sanyal and Pradeep Kumar Mallick.(2020).Deep Learning-Based Smart Attendance Monitoring System,
Proceedings of the Global AI Congress 2019(Advances in Intelligent Systems and Computing).1112,(pp.101-115). (https://doi.org/10.1007/978-981-15-2188-
1_9) (Scopus)

11. Bera S, Shrivastava VK. Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification. International Journal of Remote Sensing. 2020 Apr 2;41(7):2664-83.

12. Bera S, Shrivastava VK. Effect of pooling strategy on convolutional neural network for classification of hyperspectral remote sensing images. IET Image Processing. 2020 Feb 24;14(3):480-6.

13. Chatterjee, R., Naskar, N. B. J., Sanyal, D. K. (2020) Cellular Automata-Based Pattern Classifier for Brain-state Discrimination Problem. ICIC-Express Letters, pp. 721-729. SCOPUS

14. A. K. Tripathy, P. K. Tripathy, A. G. Mohapatra, N. K. Ray and S. P. Mohanty, WeDoShare: A Ridesharing Framework in Transportation Cyber-Physical System
for Sustainable Mobility in Smart Cities. IEEE Consumer Electronics Magazine. Vol 9(4), July 2020, ISSN: 2162-2248 (SCI Indexed, Impact Factor 3.273).

15. Rautaray, S.S., Pandey, M., Gourisaria, M. K., Sharma, R., & Das, S. (2020). Paddy Crop disease prediction – A Transfer Learning Technique. International Journal of Recent Technology and Engineering, 8(6), 1490-1495.

16. Gourisaria, M. K., Das, S., Sharma, R., Rautaray, S. S., & Pandey, M. (2020). A Deep Learning Model for Malaria Disease Detection and Analysis using Deep Convolutional Neural Networks. International Journal of emerging Technologies, 11(2), 699-704. (SCOPUS)

17. Sagnika, S., Pattanaik, A., Mishra, B. S. P., & Meher, S. K. (2020). A Review on Multi-Lingual Sentiment Analysis by Machine Learning Methods. Journal of Engineering Science and Technology Review, 13(2), 154-166. (Scopus)

18. Tripathy S., Sahoo L. (2020) Improved Method for Noise Detection by DBSCAN and Angle Based Outlier Factor in High Dimensional Datasets. In: Kumar A.,Mozar S. (eds) ICCCE 2019. Lecture Notes in Electrical Engineering, vol 570. Springer, Singapore,https://doi.org/10.1007/978-981-13-8715-9_27(scopus)

19. Mallik, S., & Sahoo, A. K. (2020). A Comparison Study of Different Privacy Preserving Techniques in Collaborative Filtering Based Recommender System.
In Computational Intelligence in Data Mining (pp. 193-203). Springer, Singapore.

20. Panigrahi, K. P., Das, H., Sahoo, A. K., & Moharana, S. C. (2020). Maize Leaf Disease Detection and Classification Using Machine Learning Algorithms. In
Progress in Computing, Analytics and Networking (pp. 659-669). Springer, Singapore.

21. Mohanty, S., Moharana, S. C., Das, H., & Satpathy, S. C. (2020). QoS Aware Group-Based Workload Scheduling in Cloud Environment. In Data Engineering and Communication Technology (pp. 953-960). Springer, Singapore. Scopus Indexed

22. Das, N., & Sagnika, S. (2020). A Subjectivity Detection-Based Approach