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20202026
most citedEnhanced SCanNet with CBAM and Dice Loss for Semantic Change Detection

6 citations · 11 across the 12 of their papers we have counts for

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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…

eess.IV2024

A Novel Algorithm for Digital Lithological Mapping-Case Studies in Sri Lanka's Mineral Exploration

R. M. L. S. Ramanayake, D. C. Dammage, I. Z. M. Zumri +8

Conventional manual lithological mapping (MLM) through field surveys are resource-extensive and time-consuming. Digital lithological mapping (DLM), harnessing remotely sensed spect…

eess.IV2024

Transformer based Endmember Fusion with Spatial Context for Hyperspectral Unmixing

R. M. K. L. Ratnayake, D. M. U. P. Sumanasekara, H. M. K. D. Wickramathilaka +3

In recent years, transformer-based deep learning networks have gained popularity in Hyperspectral (HS) unmixing applications due to their superior performance. The attention mechan…

eess.IV2023

CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction

Mevan Ekanayake, Zhifeng Chen, Mehrtash Harandi +2

In Magnetic Resonance Imaging (MRI), image acquisitions are often undersampled in the measurement domain to accelerate the scanning process, at the expense of image quality. Howeve…

eess.IV2023★ 1 cited

PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI using Deep Pixel Classification

Mevan Ekanayake, Kamlesh Pawar, Gary Egan +1

Deep learning (DL) models are capable of successfully exploiting latent representations in MR data and have become state-of-the-art for accelerated MRI reconstruction. However, und…

eess.IV2022★ 1 cited

Multi-branch Cascaded Swin Transformers with Attention to k-space Sampling Pattern for Accelerated MRI Reconstruction

Mevan Ekanayake, Kamlesh Pawar, Mehrtash Harandi +2

Global correlations are widely seen in human anatomical structures due to similarity across tissues and bones. These correlations are reflected in magnetic resonance imaging (MRI)…