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Imantha Ahangama, Dulani Meedeniya, Biswajeet Pradhan, "Explainable Image Segmentation for Spatio-Temporal and Multivariate Image Data in Precipitation Nowcasting", Results in Engineering, Elsevier, vol. 26, pp. 105595, 2025. DOI: https://doi.org/10.1016/j.rineng.2025.105595
H. Dewmini, D. Meedeniya, C. Perera "Elephant Sound Classification Using Deep Learning Optimization" Sensors, vol. 25, no. 2, pp. 352, MDPI, 2025. https://doi.org/10.3390/s25020352
D. Ranmal, P. Ranasinghe, T. Paranayapa, D. Meedeniya, C. Perera, "ESC-NAS: Environment Sound Classification Using Hardware-Aware Neural Architecture Search for the Edge", Sensors vol. 24, no. 12, p. 3749, 2024. DOI: https://doi.org/10.3390/s24123749 (pdf)
P. Ranasinghe, T. Paranayapa, D. Ranmal and D. Meedeniya, "Hardware-aware Neural Architecture Search for Sound Classification in Constrained Environments," 2024 International Research Conference on Smart Computing and Systems Engineering (SCSE), Colombo, Sri Lanka, 2024, pp. 1-6, doi: https://doi.org/10.1109/SCSE61872.2024.10550556. (pdf)
T. Paranayapa, P. Ranasinghe, D. Ranmal, D. Meedeniya, C. Perera. A Comparative Study of Preprocessing and Model Compression Techniques in Deep Learning for Forest Sound Classification. Sensors, vol. 24, no. 4:1149, 2024. Doi: https://doi.org/10.3390/s24041149
M. Bandara, R. Jayasundara, I. Ariyarathne, D. Meedeniya, C. Perera, "Forest Sound Classification Dataset: FSC22", Sensors, vol. 23, no. 4:2032, pp. 1-22, 2023. https://doi.org/10.3390/s23042032
D. Meedeniya, I. Ariyarathne, M. Bandara, R. Jayasundara, C. Perera, "A Survey on Deep Learning-based Forest Environment Sound Classification at the Edge", ACM Computing Surveys, Vol. 56, No. 3, Article No. 66, pp 1–36, 2023. Doi: https://doi.org/10.1145/3618104 (Pdf)
D. A. Meedeniya, I. Mahakalanda, D.S. Lenadora, I. Perera, S.G.S. Hewawalpita, C. Abeysinghe, and S.R. Nayak. Prediction of paddy cultivation using deep learning on land cover variation for sustainable agriculture (Chapter 13). In: R.C. Poonia, V. Singh, and S.R. Nayak, editors. Deep Learning for Sustainable Agriculture. Elsevier; 2022, p. 329-359.
https://doi.org/10.1016/B978-0-323-85214-2.00009-4
I. Mahakalanda, P. Demotte, I. Perera, D. Meedeniya, W. Wijesuriya, L. Rodrigo, "Deep learning-based prediction for stand age and land utilization of rubber plantation", M. A. Khan, R. Khan, M. A. Ansari (Eds.),in: Application of Machine Learning in Smart Agriculture, Ch. 7, pp.131-156, Elsevier Academic Press, 2022. ISBN: 9780323905503, DOI: https://doi.org/10.1016/B978-0-323-90550-3.00008-4
D. A. Meedeniya, J. A. A. M Jayanetti, M. D. N. Dilini, M. H. Wickramapala, J. H. Madushanka, Land‐Use Classification with Integrated Data, in Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, M. Malarvel, S. R. Nayak, S. N. Panda, P. K Pattnaik, N. Muangnak (Eds. ), Ch. 1,pp. 1-36, John Wiley & Sons Inc, New York, United States, 2020. ISBN10 1119681804, ISBN13 9781119681809 https://doi.org/10.1002/9781119682042.ch1
J. A. A. M Jayanetti, D. A. Meedeniya, M. D. N. Dilini, M. H. Wickramapala, J. H. Madushanka, "Enhanced land cover and land use information generation from satellite imagery and foursquare data", Proceedings of the 6th International Conference on Software and Computer Applications(ICSCA 2017), pp. 149-153, ACM, New York, NY, USA, 2017. DOI: https://doi.org/10.1145/3056662.3056681 pdf
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