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6 papers · 1 filter
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…
Transmittance Multispectral Imaging for Reheated Coconut Oil Differentiation
D. Y. L. Ranasinghe, H. M. H. K. Weerasooriya, S. Herath +4
Oil reheating has a significant impact on global health due to its extensive consumption, especially in South Asia, and severe health risks. Nevertheless, food image analysis using…
Deep Learning Methods for Screening Pulmonary Tuberculosis Using Chest X-rays
Chirath Dasanayakaa, Maheshi Buddhinee Dissanayake
Tuberculosis (TB) is a contagious bacterial airborne disease, and is one of the top 10 causes of death worldwide. According to the World Health Organization (WHO), around 1.8 billi…
A Retinex based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images
Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan +4
Low light image enhancement is an important challenge for the development of robust computer vision algorithms. The machine learning approaches to this have been either unsupervise…