most citedEnhanced SCanNet with CBAM and Dice Loss for Semantic Change Detection

6 citations · 10 across the 9 of their papers we have counts for

collaborators

9 papers

cs.AI2026

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…

eess.IV2026

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…

cs.CV2026

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…

stat.AP2025

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…

eess.IV2025

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…

eess.IV2025★ 4 cited

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-…

eess.IV2025

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…

eess.IV2025★ 6 cited

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…

stat.AP2025

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…