Pamuditha Udaranga Wickramasinghe

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Design optimization of distributed energy systems has become an interest of a wider group of researchers due the capability of these systems to integrate non-dispatchable renewable energy technologies such as solar PV and wind. White box models, using line ...

A method for enforcing smoothness constraints on surface meshes produced by a Graph Convolutional Neural Network (GCNN) including the steps of reading image data from a memory, the image data including two-dimensional image data representing a three-dimens ...

CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation. However, 3D surface representations are often required for proper analysis. They can be obtained by post-processing the labeled volumes which typic ...

The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol is too expensive to implement in many real-world projects. In this study, w ...

The energy hub concept is gradually getting popular due to its capability to integrate renewable energy technologies into the energy grid with a minimum impact. Designing distributed energy hubs is a challenging task due to the coupling of optimum dispatch ...

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs). However, their use has been restricted to relatively standardized structures such as the brain ...

Pamuditha Udaranga Wickramasinghe

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Introducing reinforcement learning to the energy system design process

A method and system for enforcing smoothness constraints on surface meshes from a graph convolutional neural network

Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data

Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis

Optimum design of distributed energy hubs using hybrid surrogate models (HSM)

Object Priors for Volumetric Image Segmentation

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Probabilistic Atlases to Enforce Topological Constraints

ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging