Computer Vision
Land use research
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. 1-38, John Wiley & Sons Inc, New York, United States, 2020. https://onlinelibrary.wiley.com/doi/book/10.1002/9781119682042
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
D. A. Meedeniya, I. Mahakalanda, D. S. Lenadora, I. Perera, S. G. S Hewawalpita, C. Abeysinghe, 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. DOI: https://doi.org/10.1016/B978-0-323-85214-2.00009-4 pdf
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 ; pdf
Human tracking research
G. Gamage, I. Sudasingha, I. Perera, D. Meedeniya, “Reinstating Dlib Correlation Human Trackers Under Occlusions in Human Detection based Tracking”, 18th International Conference on Advances in ICT for Emerging Regions (ICTer), IEEE explorer, 2018, Colombo, pp. 92-98. DOI: https://doi.org/10.1109/ICTER.2018.8615551
D.A. Meedeniya,, D.A.A.C. Rathnaweera, “Enhanced Face Recognition through Variation of Principal Component Analysis (PCA)”, in Proceedings of the 2nd International Conference on Industrial and Information (ICIIS), IEEE Xplore, pp. 347-352, 2007. DOI: https://doi.org/10.1109/ICIINFS.2007.4579200
D. Pathirage, D. De Silva, S. Wickramanayake, D. Meedeniya, S. Rasnayaka, "TEZARNet: TEmporal Zero-Shot Activity Recognition Network", In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing, Communications in Computer and Information Science, vol 1969, 30th International Conference on Neural Information Processing (ICONIP), Changsha, China, pp.444--455, Springer, 2023. DOI: https://doi.org/10.1007/978-981-99-8184-7_34 (pdf)
D. Senarath, S. Tharinda, M. Vishvajith, S. Rasnayaka, S. Wickramanayake and D. Meedeniya, "BehaveFormer: A Framework with Spatio-Temporal Dual Attention Transformers for IMU-enhanced Keystroke Dynamics," IEEE International Joint Conference on Biometrics (IJCB), Ljubljana, Slovenia, 2023, pp. 1-9, DOI: https://doi.org/10.1109/IJCB57857.2023.10448997. (pdf)
S. Wickramanayake, S. Rasnayaka, M. Gamage, D. Meedeniya, I. Perera, Chapter One - Explainable artificial intelligence for enhanced living environments: A study on user perspective, ed. G. Marques, Advances in Computers, Elsevier, vol. 133, 2024, pp. 1-32, Doi: https://doi.org/10.1016/bs.adcom.2023.10.002 . ISSN 0065-2458
K. -N. Nguyen, S. Rasnayaka, S. Wickramanayake, D. Meedeniya, S. Saha and T. Sim, "Spatio-Temporal Dual-Attention Transformer for Time-Series Behavioral Biometrics," in IEEE Transactions on Biometrics, Behavior, and Identity Science, doi: https://doi.org/10.1109/TBIOM.2024.3394875. (pdf)
Vehicle detection
H. Padmasiri, R. Madurawe, C. Abeysinghe, D. Meedeniya, "Automated Vehicle Parking Occupancy Detection in Real-Time", Moratuwa Engineering Research Conference (MERCon), IEEE explorer, pp. 644-649, Moratuwa, Sri Lanka, 2020. DOI: https://doi.org/10.1109/MERCon50084.2020.9185199 pdf (Presentation)
J. Shashirangana, H. Padmasiri, D. Meedeniya, C. Perera, Automated License Plate Recognition: A Survey on Methods and Techniques, IEEE Access, vol. 9, pp. 11203-11225, 2021, DOI: https://doi.org/10.1109/ACCESS.2020.3047929
J. Shashirangana, H. Padmasiri, D. Meedeniya, C. Perera, S. R. Nayak, J. Nayak, S. Vimal, S. Kadry, "License Plate Recognition Using Neural Architecture Search for Edge Devices", in International Journal of Intelligent Systems, Special issue Complex Industrial Intelligent Systems, vol. 36, no. 7, pp. 1-38, John Wiley and Sons Ltd, 2021. https://doi.org/10.1002/int.22471 , Shareable link: https://onlinelibrary.wiley.com/share/author/SSA2DCYDYAQCIMMZTUFM?target=10.1002/int.22471
H. Padmasiri, J. Shashirangana, D. Meedeniya, O. Rana, C. Perera, “Automated License Plate Recognition for Resource-Constrained Environments”, Sensors, MDPI Multidisciplinary Digital Publishing Institute, vol. 22, no. 4:1434, 2022. DOI: https://doi.org/10.3390/s22041434 (pdf)
More... Automated Licence Plate Recognition using Edge Devices
Character Recognition
C. Abeysinghe, I. Perera, D. A. Meedeniya, “Capsule Networks for Character Recognition in Low Resource Languages”, in Machine Vision Inspection Systems: Machine Learning-Based Approaches: Volume 2, M. Malarvel, S. R. Nayak, P. K Pattnaik, S. N. Panda, (Eds.), Ch.2 ,pp. 23-46, John Wiley & Sons Inc, New York, United States, 2021. DOI: https://doi.org/10.1002/9781119786122.ch2 ISBN 1119786096, 9781119786092
Medical image analysis
D. Haputhanthri, G. Brihadiswaran, S. Gunathilaka, D. Meedeniya, S. Jayarathna, M. Jaime, Y. Jayawardena, “An EEG based Channel Optimized Classification Approach for Autism Spectrum Disorder”, Moratuwa Engineering Research Conference (MERCon), IEEE explorer, Sri Lanka, 2019. pp. 123-128. DOI = http://dx.doi.org/10.1109/MERCon.2019.8818814
S. De Silva, S. Dayarathna, G. Ariyarathne, D. Meedeniya, S. Jayarathna, “A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data”, International Journal of Online and Biomedical Engineering (iJOE), Vol. 15, No. 13, pp. 61-76 , 2019. https://doi.org/10.3991/ijoe.v15i13.10744
G. Brihadiswaran, D. Haputhanthri, S. Gunathilaka, D. Meedeniya, S. Jayarathna, “EEG-based processing and classification methodologies for Autism Spectrum Disorder: A Review”, Journal of Computer Science (JCS), vol.15, no.8, pp. 1161.1183, 2019. DOI: http://dx.doi.org/10.3844/jcssp.2019.1161.1183
I. D. Rubasinghe, D. A. Meedeniya, “Ultrasound Nerve Segmentation Using Deep Probabilistic Programming”, Journal of ICT Research and Applications, vol. 13, no. 3, pp. 241-256 , 2019, ITB Journal Publisher, ISSN: 2337-5787, DOI: http://dx.doi.org/10.5614%2Fitbj.ict.res.appl.2019.13.3.5
Rubasinghe, I. D., & Meedeniya, D. A., “Automated Neuroscience Decision Support Framework”, B. Agarwal (Eds), in Deep Learning Techniques for Biomedical and Health Informatics, Chapter 13, pp. 305-326, Elsevier, Academic Press, 2020. ISBN: 978-0-12-819061-6 DOI: https://doi.org/10.1016/B978-0-12-819061-6.00013-6
G. Ariyarathne, S. De Silva, S. Dayarathna, D. Meedeniya, S. Jayarathna, ADHD Identification using Convolutional Neural Network with Seed-based Approach for fMRI Data, 9th International Conference on Software and Computer Applications, 2020, 31-35. https://doi.org/10.1145/3384544.3384552
D. A. Meedeniya, I. D Rubasinghe, A Review of Supportive Computational Approaches for Neurological Disorder Identification, in: T. Wadhera, D. Kakkar, (Eds.), Interdisciplinary Approaches to Altering Neurodevelopmental Disorders, Chapter 16, pp. 271-302, IGI Gloabal, 2020. DOI: https://doi.org/10.4018/978-1-7998-3069-6.ch016
D. Haputhanthri, G. Brihadiswaran, S. Gunathilaka, D. Meedeniya, S. Jayarathna, M. Jaime, C. Harshaw, "Integration of Facial Thermography in EEG-based Classification of ASD", International Journal of Automation and Computing, vol.17, no. 6, pp. 837-854, December 2020. https://doi.org/10.1007/s11633-020-123-6
N. Wijethilake, M. Islam, D. Meedeniya, C. Chitraranjan, I. Perera and H. Ren, Radiogenomics of Glioblastoma: Identification of Radiomics associated with Molecular Subtypes, In: Kia S.M. et al. (eds) Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, 2nd MICCAI workshop on Radiomics and Radiogenomics in Neuro-oncology using AI (MLCN), RNO-AI 2020. LNCS, vol 12449, Springer, Cham, pp 229-239, 2020. https://doi.org/10.1007/978-3-030-66843-3_22
N. Wijethilake, D. Meedeniya, C. Chitraranjan, I. Perera, Survival prediction and risk estimation of Glioma patients using mRNA expressions, 20th IEEE Conference on Bioinformatics and Bioengineering (BIBE), Cincinnati, OH, USA, 2020, pp. 35-42, DOI: https://doi.org/10.1109/BIBE50027.2020.00014.
S. De Silva, S. Dayarathna, G. Ariyarathne, D. Meedeniya, S. Jayarathna, fMRI Feature Extraction Model for ADHD Classification Using Convolutional Neural Network. International Journal of E-Health and Medical Communications (IJEHMC), 12:1 (6), pp. 81-105, IGI Global, 2021. https://doi.org/10.4018/IJEHMC.2021010106
S. De Silva, S. Dayarathna, G. Ariyarathne, D. Meedeniya, S. Jayarathna, A. M. P. Michalek, "Computational Decision Support System for ADHD Identification", International Journal of Automation and Computing (IJAC), vol. no. pp. 2021. DOI: https://doi.org/10.1007/s11633-020-1252-1 (pdf)
N. Wijethilake, D. Meedeniya, C. Chitraranjan, I. Perera, M. Islam and H. Ren, "Glioma Survival Analysis Empowered with Data Engineering - A Survey", IEEE Access, vol. 9, pp. 43168-43191, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3065965
L. Herath, D. Meedeniya, M.A.J.C Marasingha, V. Weerasinghe, "Autism Spectrum Disorder Diagnosis Support Model Using InceptionV3", International Research Conference on Smart Computing and Systems Engineering (SCSE), Kelaniya, Sri Lanka, 2021, pp. 1-7 . DOI: https://doi.org/10.1109/SCSE53661.2021.9568314 pdf (Best Paper) (Presentation)
S. Kolonne, H. Kumarasinghe, C. Fernando, D. Meedeniya, "MobileNetV2 Based Chest X-Rays Classification", International Conference on Decision Aid Sciences and Application (DASA), Bahrain, 2021, pp. 57-61, DOI: 10.1109/DASA53625.2021.9682248 (pdf) (Presentation)
L. Herath, D. Meedeniya, J. Marasingha and V. Weerasinghe, "Optimize Transfer Learning for Autism Spectrum Disorder Classification with Neuroimaging: A Comparative Study," 2nd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2022, pp. 171-176, DOI: http://dx.doi.org/10.1109/ICARC54489.2022.9753949. (pdf) (Presentation)
C. Fernando, S. Kolonne, H. Kumarasinghe and D. Meedeniya, "Chest Radiographs Classification Using Multi-model Deep Learning: A Comparative Study," 2nd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2022, pp. 165-170, DOI: http://dx.doi.org/10.1109/ICARC54489.2022.9753811. (pdf) (Presentation)
T. Shyamalee and D. Meedeniya, "CNN Based Fundus Images Classification For Glaucoma Identification," 2nd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2022, pp. 200-205, DOI: http://dx.doi.org/10.1109/ICARC54489.2022.9754171. (pdf) (Presentation)
S. Dasanayaka, S. Silva, V. Shantha, D. Meedeniya and T. Ambegoda, "Interpretable Machine Learning for Brain Tumor Analysis Using MRI," 2nd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2022, pp. 212-217, DOI: http://dx.doi.org/10.1109/ICARC54489.2022.9754131. (pdf) (Presentation)
T. Shyamalee and D. Meedeniya, "Attention U-Net for Glaucoma Identification Using Fundus Image Segmentation," 2022 International Conference on Decision Aid Sciences and Applications (DASA), Chiangrai, Thailand, 2022, pp. 6-10, doi: https://doi.org/10.1109/DASA54658.2022.9765303. (pdf) (Presentation)
S. de Silva, S. Dayarathna, & D. Meedeniya, Alzheimer’s Disease Diagnosis using Functional and Structural Neuroimaging Modalities, Wadhera, T., & Kakkar, D. (Eds), in Enabling Technology for Neurodevelopmental Disorders: from Diagnosis to Rehabilitation, Ch. 11, pp. 162—183, Routledge, Taylor & Francis CRS Press, 2022. DOI: http://dx.doi.org/10.4324/9781003165569-11 eBook ISBN 9781003165569; pdf
K. A. S. H. Kumarasinghe, S. L. Kolonne, K. C. M. Fernando, D. Meedeniya, U-Net Based Chest X-ray Segmentation with Ensemble Classification for Covid-19 and Pneumonia, International Journal of Online and Biomedical Engineering (iJOE), Vol. 18, No. 7, pp. 161-174, 2022. DOI: https://doi.org/10.3991/ijoe.v18i07.30807
S. Dasanayaka, V. Shantha, S. Anupa Silva, D. Meedeniya and T. Ambegoda, Interpretable Machine Learning for Brain Tumour Analysis using MRI and Whole Slide Images, Software Impacts, vol. 13, pp. 100340, 2022, DOI:https://doi.org/10.1016/j.simpa.2022.100340 (pdf)
D. Meedeniya, H. Kumarasinghe, S. Kolonne, C. Fernando, I. De la Torre Díez, G. Marques, “Chest X-ray Analysis Empowered with Deep Learning: A Systematic Review”, Applied Soft Computing, vol. 126, pp. 109319, 2022. DOI: https://doi.org/10.1016/j.asoc.2022.109319. (pdf)
T. Shyamalee and D. Meedeniya, “Glaucoma Detection with Retinal Fundus Images Using Segmentation and Classification”, Machine Intelligence Research, vol. 19, no. 6, pp. 563-580, 2022. DOI: http://doi.org/10.1007/s11633-022-1354-z (pdf)
W. Nimalsiri, M. Hennayake, K. Rathnayake, T. D. Ambegoda and D. Meedeniya, "Automated Radiology Report Generation Using Transformers," Proceedings of the 3rd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2023, pp. 90-95, doi: https://doi.org/10.1109/ICARC57651.2023.10145699. (Pdf) (Best Paper Award) - Computer Vision and Image Processing Track (Presentation)
L. Gamage, U. Isuranga, S. De Silva and D. Meedeniya, "Melanoma Skin Cancer Classification with Explainability," Proceedings of the 3rd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2023, pp. 30-35, doi: https://doi.org/10.1109/ICARC57651.2023.10145622. (Pdf) (Presentation)
T. Shyamalee, D. Meedeniya, G. Lim and M. Karunarathne, "Automated Tool Support for Glaucoma Identification With Explainability Using Fundus Images," in IEEE Access, vol. 12, pp. 17290-17307, 2024, doi: https://doi.org/10.1109/ACCESS.2024.3359698.
T. Wanasinghe, S. Bandara, S. Madusanka, D. Meedeniya, M. Bandara and I. d. l. T. Díez, "Lung Sound Classification with Multi-Feature Integration Utilizing Lightweight CNN Model," IEEE Access, vol. 12, pp. 21262 - 21276, 2024. doi: https://doi.org/10.1109/ACCESS.2024.3361943.
L. Gamage, U. Isuranga, D. Meedeniya, S. De Silva, and P. Yogarajah, "Melanoma Skin Cancer Identification with Explainability Utilizing Mask Guided Technique" Electronics, vol. 13, no. 4: 680, 2024. Doi: https://doi.org/10.3390/electronics13040680
N. Gnanavel, P. Inparaj, N. Sritharan, D. Meedeniya and P. Yogarajah, "Interpretable Cervical Cell Classification: A Comparative Analysis," 2024 4th International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2024, pp. 7-12, doi: https://doi.org/10.1109/ICARC61713.2024.10499737.
N. Sritharan, N. Gnanavel, P. Inparaj, D. Meedeniya and P. Yogarajah, "EnsembleCAM: Unified Visualization for Explainable Cervical Cancer Identification," 2024 International Research Conference on Smart Computing and Systems Engineering (SCSE), Colombo, Sri Lanka, 2024, pp. 1-6, doi: https://doi.org/10.1109/SCSE61872.2024.10550859. (pdf)
Face Recognition
D.A. Meedeniya,, D.A.A.C. Rathnaweera, “Face Recognition using a variation of principle component analysis technique”, in Proceedings of the University of Peradeniya Research Session, Vol 11, 2006. http://dlib.pdn.ac.lk/handle/123456789/3543
D.A. Meedeniya,, D.A.A.C. Rathnaweera, “Enhanced Face Recognition through Variation of Principal Component Analysis (PCA)”, in Proceedings of the 2nd International Conference on Industrial and Information (ICIIS), IEEE Xplore, pp. 347-352, 2007. DOI: 10.1109/ICIINFS.2007.4579200 pdf
Eye Gaze Estimation
P. Pathirana, S. Senarath, D. Meedeniya and S. Jayarathna, "Single-User 2D Gaze Estimation in Retail Environment Using Deep Learning," 2nd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2022, pp. 206-211, DOI: http://dx.doi.org/10.1109/ICARC54489.2022.9754167. (pdf)
S. Senarath, P. Pathirana, D. Meedeniya and S. Jayarathna, "Retail Gaze: A Dataset for Gaze Estimation in Retail Environments," 2022 International Conference on Decision Aid Sciences and Applications (DASA), Chiangrai, Thailand, 2022, pp. 1040-1044, doi: https://doi.org/10.1109/DASA54658.2022.9765224. (pdf) (Presentation)
P. Pathirana, S. Senarath, D. Meedeniya, S. Jayarathna, "Eye Gaze Estimation: A Survey on Deep Learning-Based Approaches", Expert Systems with Applications, Elsevier, 2022, vol. 199 , no. 116894, pp. 1-16. DOI: https://doi.org/10.1016/j.eswa.2022.116894 , URL: https://www.sciencedirect.com/science/article/pii/S0957417422003347, ISSN: 0957-4174 pdf
S. Senarath, P. Pathirana, D. Meedeniya and S. Jayarathna, “Customer Gaze Estimation in Retail Using Deep Learning”, IEEE Access, vol. 10, pp. 64904-64919, 2022. DOI: https://doi.org/10.1109/ACCESS.2022.3183357 (Presentation)
Retail Gaze: Gaze Estimation in Retail Environment , IEEE Dataport
Human Computer Interaction
D. Senarath, S. Tharinda, M. Vishvajith, S. Rasnayaka, S. Wickramanayake and D. Meedeniya, "Re-evaluating Keystroke Dynamics for Continuous Authentication," Proceedings of the 3rd International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2023, pp. 202-207, doi: https://doi.org/10.1109/ICARC57651.2023.10145743. (Best Paper Award) - 'Human-Computer Interaction and Computer Vision Track’