Dr Sujit Biswas
Name | Dr Sujit Biswas |
---|---|
ORCID | https://orcid.org/0000-0002-6770-9845 |
Job title | Lecturer |
Email address | s.biswas3@uel.ac.uk |
Research institute | Architecture, Computing & Engineering |
Research outputs
Impact learning: A learning method from feature’s impact and competition
Prottasha, N. J., Murad, S. A., Muzahid, A. J. M., Rana, M., Kowsher, M., Adhikary, A., Biswas, S. and Bairagi, A. K. 2023. Impact learning: A learning method from feature’s impact and competition. Journal of Computational Science. 69 (Art. 102011). https://doi.org/10.1016/j.jocs.2023.102011Interoperability Benefits and Challenges in Smart City Services: Blockchain as a Solution
Biswas, S., Yao, Z., Yan, L., Alqhatani, A., Bairagi, A. K., Asiri, F. and Masud, M. 2023. Interoperability Benefits and Challenges in Smart City Services: Blockchain as a Solution. Electronics. 12 (4), p. Art. 1036. https://doi.org/https://doi.org/10.3390/electronics12041036A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks
Latif, Z., Umer, Q., Lee, C., Sharif, K., Li, F. and Biswas, S. 2022. A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks. Sensors. 22 (21), p. Art. 8434. https://doi.org/10.3390/s22218434Blockchain Empowered Federated Learning Ecosystem for Securing Consumer IoT Features Analysis
Alghamdi, A., Zhu, J., Yin, G., Shorfuzzaman, M., Alsufyani, N., Alyami, S. and Biswas, S. 2022. Blockchain Empowered Federated Learning Ecosystem for Securing Consumer IoT Features Analysis. Sensors. 22 (18), p. 6786. https://doi.org/10.3390/s2218678674
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