Nalinda Somasiri
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- Ratnayake, Upadya, Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Pokhrel, Sangita ORCID: https://orcid.org/0009-0008-2092-7029 (2023) Enhancing CNN Models with Data Augmentation for Accurate Fertilizer Deficiencies and Diseases Identification in Paddy Crops. In: International Conference on Business Innovation 2023 (ICOBI 2023). ICOBI, pp. 575-582
- Karunarathne, Lakmali ORCID: https://orcid.org/0009-0000-7720-7817, Sihan, Haroon Muhammed, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 (2023) Determine What the Student Understands-Assessment in An Un-scaffolded Environment. In: International Conference on Business Innovation 2023 (ICOBI 2023) proceedings. ICOBI, pp. 330-335
- Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251, Wickramasinghe, Shammika ORCID: https://orcid.org/0009-0001-7502-802X and Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 (2023) Deep Learning Model Regression Based Object Detection for Adaptive Driving Beam Headlights. In: Proceedings of the 2023 8th International Conference on Machine Learning Technologies. ACM, pp. 235-239
- Karunarathne, Lakmali ORCID: https://orcid.org/0009-0000-7720-7817, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 (2023) Business During COVID: An IOT Based Automated Sand Truck Management Solution. SSRN Electronic Journal, 13 (10).
- Singarathnam, Dharshika, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090, Pokhrel, Sangita ORCID: https://orcid.org/0009-0008-2092-7029 and Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 (2023) Machine learning-based predictive models for cardiovascular risk assessment in data analysis, model development, and clinical implications. International Journal of Recent Advances in Multidisciplinary Research, 10 (10). pp. 9084-9089.
- Singarathnam, Dharshika, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090, Pokhrel, Sangita ORCID: https://orcid.org/0009-0008-2092-7029 and Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 (2023) Exploring Cryptographic Techniques for Data security in Resource-Constrained Wireless Sensor Networks:Performance Evaluation and Considerations. In: 2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS). IEEE, pp. 176-180
- Karunarathne, Lakmali ORCID: https://orcid.org/0009-0000-7720-7817, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 (2023) Business during COVID: An IOT (Internet of Things) based Automated Sand Truck Management Solution. In: 5th International Conference on Internet of Things (CIoT 2023), 17 June 2023, Sydney, Australia. (Unpublished)
- Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Wicramasinghe, Shammika (2023) Deep Learning Model Regression Based Object Detection for Adaptive Driving Beam Headlights. In: 2023 8th International Conference on Machine Learning Technologies (ICMLT 2023), 10 March 2023, Sweden.
- Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251, Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090 and Wicramasinghe, Shammika (2022) Deep Learning Model Regression Based Object Detection for Adaptive Driving Beam Headlights. In: 2023 8th International Conference on Machine Learning Technologies (ICMLT 2023), 10 March 2023, Sweden. (Submitted)
- Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090, Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251, Jeyavadhanam, Rebecca and Karthick, Gayathri (2023) Improved Computational Efficiency of Machine Learning Algorithm based on Evaluation Metrics to control the spread of Coronavirus in the UK. In: ICDSTA 2023: 17. International Conference on Data Science Techniques and Applications, 16-17th February, 2023, London.
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