27 citations · 50 across the 34 of their papers we have counts for
39 papers
ChangeT: Evaluating Vision Test-Time Training for Remote Sensing Change Detection
Sharukshan Niranjan, Oshadha Samarakoon, Nichula Wasalathilaka +3
Bitemporal remote sensing change detection requires representations that preserve spatial detail while capturing contextual information relevant to changes between acquisitions. Vi…
Local Consistency Does Not Guarantee Global Conservation: Auditing Zero-Shot Composition of Airway Flow Operators
Nichula Sathmith Wasalathilaka, Navodya Heshan Samarasinghe Dhanujaya Suraweera, Kevin Dawson +2
Neural operators approximate PDE solutions within a geometry family, but independently learned local operators need not form a consistent global simulator. We study frozen, single-…
Empirical mode decomposition and interpretable machine learning for preterm birth classification from electrohysterography
Umesha Tilakarathna, Senith Jayakody, Kalana Jayasooriya +4
Preterm birth (PTB) remains a major global health problem, and reliable non-invasive risk assessment remains difficult. Electrohysterography (EHG) records uterine electrical activi…
Non-Destructive Quantification of Urea Adulteration in Bovine Milk Using Transmittance Multispectral Imaging
Sharukshan Niranjan, Iresha Ranaweera, Tharindu Chandrarathne +5
Adulteration of bovine milk using urea remains a major food quality and health concern, motivating the development of rapid and quantitative screening tools. Conventional approache…
A Synchronized Multi-IMU Wearable System for Tracking of Joint-Angles in Sports Motion Analysis With Reference-Based Validation and Dynamic Task Characterization
Thevindu Samarasekera, Praveen Rathnayaka, Sachintha Adhikari +7
Reliable joint-angle measurement outside laboratory environments is important for posture assessment and technique analysis in sports and rehabilitation. Yet, wearable IMU systems,…
A Controlled Visual-Backbone Benchmark for Multimodal Short-Term Solar Irradiance Forecasting
Oshadha Samarakoon, Dushan Herath, Ishara Ranmandala +4
Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and training recipe all change together.…
Structure over Depth: A Single-Block Spatio-Temporal Transformer for Multi-Entity Reasoning
Narthana Sivalingam, Santhirarajah Sivasthigan, Buddhi Wijenayake +3
Modeling multi-entity temporal data requires capturing dependencies across entities, time, and their interactions. Transformer-based approaches perform well but often rely on deep…
MambaRefine-CD: MambaVision with Region-Boundary Temporal Refinement
Dineth Perera, Thaariq Firdous, Oshadha Samarakoon +3
Binary change detection in remote sensing requires both complete changed-region localization and accurate boundary delineation. We present MambaRefine-CD, a region-boundary tempora…
ScaLe-INR: Scale and Learn Implicit Neural Representations
Buwaneka Epakanda, Athulya Ratnayake, Pandula Thennakoon +4
Implicit Neural Representations (INRs) parameterized by multilayer perceptrons excel at modeling continuous signals. However, a key challenge persists as INRs fundamentally suffer…
RespGeomLib: A Reproducible Parametric Engine for Generating Analysis-Ready Human Airway Lumen Geometry
Nichula Wasalathilaka, Parakrama Ekanayake, Roshan Godaliyadda
CT-derived airway models support pulmonary morphometry and airflow simulation, but are often limited by distal scan resolution and the need for substantial cleanup near bifurcation…
A Controlled Benchmark of Visual State-Space Backbones with Domain-Shift and Boundary Analysis for Remote-Sensing Segmentation
Nichula Wasalathilaka, Dineth Perera, Oshadha Samarakoon +4
Visual state-space models (SSMs) are increasingly promoted as efficient alternatives to Vision Transformers, yet their practical advantages remain unclear under fair comparison bec…
Mitigating Long-Tail Bias via Prompt-Controlled Diffusion Augmentation
Buddhi Wijenayake, Nichula Wasalathilake, Roshan Godaliyadda +3
Long-tailed class imbalance remains a fundamental obstacle in semantic segmentation of high-resolution remote-sensing imagery, where dominant classes shape learned representations…
PoPStat-COVID19: Leveraging Population Pyramids to Quantify Demographic Vulnerability to COVID-19
Buddhi Wijenayake, Athulya Ratnayake, Lelumi Edirisinghe +8
Understanding how population age structure shapes COVID-19 burden is crucial for pandemic preparedness, yet common summary measures such as median age ignore key distributional fea…
Spectrotemporal Feature Extraction in EHG Signals and Tocograms for Enhanced Preterm Birth Prediction
Senith Jayakody, Kalana Jayasooriya, Sashini Liyanage +3
Preterm birth (PTB), defined as delivery before 37 weeks of gestation, is a leading cause of neonatal mortality and long term health complications. Early detection is essential for…
Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance
Praveen Sumanasekara, Athulya Ratnayake, Buddhi Wijenayake +4
Spectral variability significantly impacts the accuracy and convergence of hyperspectral unmixing algorithms. Many methods address complex spectral variability; yet large-scale dis…
Mamba-FCS: Joint Spatio- Frequency Feature Fusion, Change-Guided Attention, and SeK Loss for Enhanced Semantic Change Detection in Remote Sensing
Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara +4
Semantic Change Detection (SCD) from remote sensing imagery requires models balancing extensive spatial context, computational efficiency, and sensitivity to class-imbalanced land-…
Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara +5
Remote sensing change detection is vital for monitoring environmental and urban transformations but faces challenges like manual feature extraction and sensitivity to noise. Tradit…
COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representations
Pandula Thennakoon, Avishka Ranasinghe, Mario De Silva +4
Implicit neural representations (INRs) are a powerful paradigm for modeling data, offering a continuous alternative to discrete signal representations. Their ability to compactly e…
AVSim -- Realistic Simulation Framework for Airborne and Vector-Borne Disease Dynamics
Pandula Thennakoon, Mario De Silva, M. Mahesha Viduranga +8
Computational disease modeling plays a crucial role in understanding and controlling the transmission of infectious diseases. While agent-based models (ABMs) provide detailed insig…
The Role of Social Interactions in Mitigating Psychological Distress During the COVID-19 Pandemic: A Study in Sri Lanka
Isuru Thilakasiri, Tharaka Fonseka, Isuri Mapa +6
Massive changes in many aspects related to social groups of different socioeconomic backgrounds were caused by the COVID-19 pandemic and as a result, the overall state of mental he…
Devising PoPStat: A Metric Bridging Population Pyramids with Global Disease Mortality
Tharaka Fonseka, Buddhi Wijenayake, Athulya Ratnayake +7
Understanding the relationship between population dynamics and disease-specific mortality is central to evidence-based health policy. This study introduces two novel metrics, PoPDi…
Impact of Shoe Parameters on Gait Using Wearables
Nadeera Meghapathirana, Oshada Rathnayake, Thisali S Rathnayake +3
The study of biomechanics during locomotion provides valuable insights into the effects of varying conditions on specific movement patterns. This research focuses on examining the…
Performance Benchmarking of Psychomotor Skills Using Wearable Devices: An Application in Sport
Mahela Pandukabhaya, Tharaka Fonseka, Madhumini Kulathunge +4
Mastering psychomotor skills, such as those essential in sports, rehabilitation, and professional training, often requires a precise understanding of motion patterns and performanc…
DE-LIoT: The Data-Energy Networking Paradigm for Sustainable Light-Based Internet of Things
Amila Perera, Roshan Godaliyadda, Marcos Katz
The growing demand for Internet of Things (IoT) networks has sparked interest in sustainable, zero-energy designs through Energy Harvesting (EH) to extend the lifespans of IoT sens…