
A Topological Loss Function for DeepLearning based Image Segmentation using Persistent Homology
We introduce a method for training neural networks to perform image or v...
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ModelBased and DataDriven Strategies in Medical Image Computing
Modelbased approaches for image reconstruction, analysis and interpreta...
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dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
AUTOMAP is a promising generalized reconstruction approach, however, it ...
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Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A datadriven approach to Predict Brain Age from Cortical Anatomical Measures
The use of machine learning (ML) algorithms has significantly increased ...
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Topologypreserving augmentation for CNNbased segmentation of congenital heart defects from 3D paediatric CMR
Patientspecific 3D printing of congenital heart anatomy demands an accu...
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Data consistency networks for (calibrationless) accelerated parallel MR image reconstruction
We present simple reconstruction networks for multicoil data by extendi...
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VFCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation
Atrial Fibrillation (AF) is a common electrophysiological cardiac disor...
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Aleatoric uncertainty estimation with testtime augmentation for medical image segmentation with convolutional neural networks
Despite the stateoftheart performance for medical image segmentation,...
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Stochastic Filter Groups for MultiTask CNNs: Learning Specialist and Generalist Convolution Kernels
The performance of multitask learning in Convolutional Neural Networks ...
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Spectral Multiscale Community Detection in Temporal Networks with an Application
The analysis of temporal networks has a wide area of applications in a w...
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Explaining Deep Neural Networks Using SpectrumBased Fault Localization
Deep neural networks (DNNs) increasingly replace traditionally developed...
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Channel Assignment in Uplink Wireless Communication using Machine Learning Approach
This letter investigates a channel assignment problem in uplink wireless...
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A Survey of Conventional and Artificial Intelligence / Learning based Resource Allocation and Interference Mitigation Schemes in D2D Enabled Networks
5th generation networks are envisioned to provide seamless and ubiquitou...
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Automatic Brain Tumor Segmentation using Convolutional Neural Networks with TestTime Augmentation
Automatic brain tumor segmentation plays an important role for diagnosis...
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3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects
Extremely small objects (ESO) have become observable on clinical routine...
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Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs
In this paper, the problem of optimizing the deployment of unmanned aeri...
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Oversegmenting Graphs
We propose a novel method to adapt a graph to image data. The method dri...
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Structured MultiLabel Biomedical Text Tagging via Attentive Neural Tree Decoding
We propose a model for tagging unstructured texts with an arbitrary numb...
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Global and Local Interpretability for Cardiac MRI Classification
Deep learning methods for classifying medical images have demonstrated i...
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Testtime augmentation with uncertainty estimation for deep learningbased medical image segmentation
Data augmentation has been widely used for training deep learning system...
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Automatic CNNbased detection of cardiac MR motion artefacts using kspace data augmentation and curriculum learning
Good quality of medical images is a prerequisite for the success of subs...
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Learning joint lesion and tissue segmentation from taskspecific heteromodal datasets
Brain tissue segmentation from multimodal MRI is a key building block of...
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HeteroModal Variational EncoderDecoder for Joint Modality Completion and Segmentation
We propose a new deep learning method for tumour segmentation when deali...
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Robotic Tactile Perception of Object Properties: A Review
Touch sensing can help robots understand their sur rounding environment...
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A Brief Introduction to Machine Learning for Engineers
This monograph aims at providing an introduction to key concepts, algori...
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CASP Solutions for Planning in Hybrid Domains
CASP is an extension of ASP that allows for numerical constraints to be ...
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Extracting Lifted Mutual Exclusion Invariants from Temporal Planning Domains
We present a technique for automatically extracting mutual exclusion inv...
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Two forms of minimality in ASPIC+
Many systems of structured argumentation explicitly require that the fac...
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On the links between argumentationbased reasoning and nonmonotonic reasoning
In this paper we investigate the links between instantiated argumentatio...
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PDDL+ Planning via Constraint Answer Set Programming
PDDL+ is an extension of PDDL that enables modelling planning domains wi...
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Phase Diagram of Restricted Boltzmann Machines and Generalised Hopfield Networks with Arbitrary Priors
Restricted Boltzmann Machines are described by the Gibbs measure of a bi...
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Random Forest regression for manifoldvalued responses
An increasing array of biomedical and computer vision applications requi...
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Learning what to look in chest Xrays with a recurrent visual attention model
Xrays are commonly performed imaging tests that use small amounts of ra...
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A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
Inspired by recent advances in deep learning, we propose a framework for...
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Gaussian Processes for Survival Analysis
We introduce a semiparametric Bayesian model for survival analysis. The...
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Modelling Radiological Language with Bidirectional Long ShortTerm Memory Networks
Motivated by the need to automate medical information extraction from fr...
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Deep metric learning for multilabelled radiographs
Many radiological studies can reveal the presence of several coexisting...
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Theory of SemiInstantiation in Abstract Argumentation
We study instantiated abstract argumentation frames of the form (S,R,I),...
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Probabilistic Argumentation. An Equational Approach
There is a generic way to add any new feature to a system. It involves 1...
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The Computational Complexity of StructureBased Causality
Halpern and Pearl introduced a definition of actual causality; Eiter and...
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Equilibrium States in Numerical Argumentation Networks
Given an argumentation network with initial values to the arguments, we ...
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Abduction and Dialogical Proof in Argumentation and Logic Programming
We develop a model of abduction in abstract argumentation, where changes...
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Learning population and subjectspecific brain connectivity networks via Mixed Neighborhood Selection
In neuroimaging data analysis, Gaussian graphical models are often used ...
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Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks
Pattern recognition methods using neuroimaging data for the diagnosis of...
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Measuring the functional connectome "onthefly": towards a new control signal for fMRIbased braincomputer interfaces
There has been an explosion of interest in functional Magnetic Resonance...
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Dimensionality Detection and Integration of Multiple Data Sources via the GPLVM
The Gaussian Process Latent Variable Model (GPLVM) is a nonlinear prob...
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Interpolation in Equilibrium Logic and Answer Set Programming: the Propositional Case
Interpolation is an important property of classical and many non classic...
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Random walk kernels and learning curves for Gaussian process regression on random graphs
We consider learning on graphs, guided by kernels that encode similarity...
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Learning curves for multitask Gaussian process regression
We study the average case performance of multitask Gaussian process (GP...
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RationaleAugmented Convolutional Neural Networks for Text Classification
We present a new Convolutional Neural Network (CNN) model for text class...
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