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View article: A scoping review of machine learning applications in power system protection and disturbance management
A scoping review of machine learning applications in power system protection and disturbance management Open
The integration of renewable and distributed energy resources reshapes modern power systems, challenging conventional protection schemes. This scoping review synthesizes recent literature on machine learning (ML) applications in power syst…
View article: Benchmarking Machine Learning Models for Fault Classification and Localization in Power System Protection
Benchmarking Machine Learning Models for Fault Classification and Localization in Power System Protection Open
The increasing integration of distributed energy resources (DERs), particularly renewables, poses significant challenges for power system protection, with fault classification (FC) and fault localization (FL) being among the most critical …
View article: Water Demand Forecasting of District Metered Areas through Learned Consumer Representations
Water Demand Forecasting of District Metered Areas through Learned Consumer Representations Open
Advancements in smart metering technologies have significantly improved the ability to monitor and manage water utilities. In the context of increasing uncertainty due to climate change, securing water resources and supply has emerged as a…
View article: Battle of Water Demand Forecasting
Battle of Water Demand Forecasting Open
As part of the Battle of Water Networks competition series, the Battle of Water Demand Forecasting (BWDF) was organized in the context of the 3rd Water Distribution Systems Analysis and Computing and Control in the Water Industry (WDSA-CCW…
View article: Impact of Data Sparsity on Machine Learning for Fault Detection in Power System Protection
Impact of Data Sparsity on Machine Learning for Fault Detection in Power System Protection Open
Germany's transition to a renewable energy-based power system is reshaping grid operations, requiring advanced monitoring and control to manage decentralized generation. Machine learning (ML) has emerged as a powerful tool for power system…
View article: Learning Wavelet-Sparse FDK for 3D Cone-Beam CT Reconstruction
Learning Wavelet-Sparse FDK for 3D Cone-Beam CT Reconstruction Open
Cone-Beam Computed Tomography (CBCT) is essential in medical imaging, and the Feldkamp-Davis-Kress (FDK) algorithm is a popular choice for reconstruction due to its efficiency. However, FDK is susceptible to noise and artifacts. While rece…
View article: Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography
Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography Open
Optimal selection of X-ray imaging parameters is crucial in coronary angiography and structural cardiac procedures to ensure optimal image quality and minimize radiation exposure. These anatomydependent parameters are organized into custom…
View article: Advancing Heat Demand Forecasting with Attention Mechanisms: Opportunities and Challenges
Advancing Heat Demand Forecasting with Attention Mechanisms: Opportunities and Challenges Open
Global leaders and policymakers are unified in their unequivocal commitment to decarbonization efforts in support of Net-Zero agreements. District Heating Systems (DHS), while contributing to carbon emissions due to the continued reliance …
View article: A Self-supervised Multimodal Deep Learning Approach to Differentiate Post-radiotherapy Progression from Pseudoprogression in Glioblastoma
A Self-supervised Multimodal Deep Learning Approach to Differentiate Post-radiotherapy Progression from Pseudoprogression in Glioblastoma Open
Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma (GBM) patients is crucial for optimal treatment planning. However, this task remains challenging due to the overlapp…
View article: Compensating CBCT Motion Artifacts with Any 2D Generative Model
Compensating CBCT Motion Artifacts with Any 2D Generative Model Open
This paper presents a novel approach to mitigate motion artifacts in industrial Cone-Beam Computed Tomography (CBCT) caused by detector or X-ray source jitter due to mechanical vibration. Leveraging two-dimensional (2D) generative models w…
View article: Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram
Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram Open
Water management is vital for building an adaptive and resilient society. Water demand forecasting aids water management by learning the underlying relationship between consumption and governing variables for optimal supply. In this paper,…
View article: Attention-Guided Erasing for Enhanced Transfer Learning in Breast Abnormality Classification
Attention-Guided Erasing for Enhanced Transfer Learning in Breast Abnormality Classification Open
Purpose: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation tec…
View article: EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction
EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction Open
Computed Tomography (CT) image reconstruction is crucial for accurate diagnosis and deep learning approaches have demonstrated significant potential in improving reconstruction quality. However, the choice of loss function profoundly affec…
View article: Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series Open
In this study, we introduce a Fourier series-based trainable filter for computed tomography (CT) reconstruction within the filtered backprojection (FBP) framework. This method overcomes the limitation in noise reduction by optimizing Fouri…
View article: Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification
Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification Open
The assessment of breast density is crucial in the context of breast cancer screening, especially in populations with a higher percentage of dense breast tissues. This study introduces a novel data augmentation technique termed Attention-G…
View article: Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble Open
One of the primal challenges faced by utility companies is ensuring efficient supply with minimal greenhouse gas emissions. The advent of smart meters and smart grids provide an unprecedented advantage in realizing an optimised supply of t…
View article: Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model
Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model Open
In combating climate change, an effective demand-based energy supply operation of the district energy system (DES) for heating or cooling is indispensable. As a consequence, an accurate forecast of heat consumption on the consumer side pos…
View article: Implications of Experiment Set-Ups for Residential Water End-Use Classification
Implications of Experiment Set-Ups for Residential Water End-Use Classification Open
With an increasing need for secured water supply, a better understanding of the water consumption behavior is beneficial. This can be achieved through end-use classification, i.e., identifying end-uses such as toilets, showers or dishwashe…
View article: Implications of Experiment Set-Ups for Residential Water End-Use Classification
Implications of Experiment Set-Ups for Residential Water End-Use Classification Open
With the increased population in urban areas worldwide, the security of water supply is gaining in importance. Water scarcity accelerated by climate change poses additional stress to water supply infrastructures. Water consumption data tra…
View article: An Investigation of Feature-based Nonrigid Image Registration using\n Gaussian Process
An Investigation of Feature-based Nonrigid Image Registration using\n Gaussian Process Open
For a wide range of clinical applications, such as adaptive treatment\nplanning or intraoperative image update, feature-based deformable registration\n(FDR) approaches are widely employed because of their simplicity and low\ncomputational …
View article: Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach Open
Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions. The differences between intra-patient images can be asses…
View article: Analyzing an Imitation Learning Network for Fundus Image Registration\n Using a Divide-and-Conquer Approach
Analyzing an Imitation Learning Network for Fundus Image Registration\n Using a Divide-and-Conquer Approach Open
Comparison of microvascular circulation on fundoscopic images is a\nnon-invasive clinical indication for the diagnosis and monitoring of diseases,\nsuch as diabetes and hypertensions. The differences between intra-patient\nimages can be as…
View article: Corrigendum to “Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery”
Corrigendum to “Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery” Open
[This corrects the article DOI: 10.1155/2017/6028645.].
View article: Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery
Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery Open
Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this p…