9 papers
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…
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…
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…
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…
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-…
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…