6 papers
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…
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…
Enhanced SCanNet with CBAM and Dice Loss for Semantic Change Detection
Athulya Ratnayake, Buddhi Wijenayake, Praveen Sumanasekara +3
Semantic Change Detection (SCD) in remote sensing imagery requires accurately identifying land-cover changes across multi-temporal image pairs. Despite substantial advancements, in…
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…