
NetCut: RealTime DNN Inference Using Layer Removal
Deep Learning plays a significant role in assisting humans in many aspec...
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Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand
For lower arm amputees, prosthetic hands promise to restore most of phys...
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Universal Physiological Representation Learning with SoftDisentangled Rateless Autoencoders
Human computer interaction (HCI) involves a multidisciplinary fusion of ...
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Disentangled Adversarial Autoencoder for SubjectInvariant Physiological Feature Extraction
Recent developments in biosignal processing have enabled users to exploi...
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Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry
Systems that are based on recursive Bayesian updates for classification ...
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AutoBayes: Automated Inference via Bayesian Graph Exploration for NuisanceRobust Biosignal Analysis
Learning data representations that capture taskrelated features, but ar...
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Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI
Posttraumatic epilepsy (PTE) is a lifelong complication of traumatic b...
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Disentangled Adversarial Transfer Learning for Physiological Biosignals
Recent developments in wearable sensors demonstrate promising results fo...
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Active Recursive Bayesian Inference with Posterior Trajectory Analysis Using αDivergence
Recursive Bayesian inference (RBI) provides optimal Bayesian latent vari...
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Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach
A deep neural network (DNN) that can reliably model muscle responses fro...
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UserAdaptive Text Entry for Augmentative and Alternative Communication
The viability of an Augmentative and Alternative Communication device of...
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Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects
Across and withinrecording variabilities in electroencephalographic (E...
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Information Theoretic Feature Transformation Learning for Brain Interfaces
Objective: A variety of pattern analysis techniques for model training i...
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Adversarial Deep Learning in EEG Biometrics
Deep learning methods for person identification based on electroencephal...
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Accelerated Experimental Design for Pairwise Comparisons
Pairwise comparison labels are more informative and less variable than c...
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Transfer Learning in BrainComputer Interfaces with Adversarial Variational Autoencoders
We introduce adversarial neural networks for representation learning as ...
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TimeSeries Prediction of Proximal Aggression Onset in MinimallyVerbal Youth with Autism Spectrum Disorder Using Physiological Biosignals
It has been suggested that changes in physiological arousal precede pote...
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Hierarchical Graphical Models for ContextAware Hybrid BrainMachine Interfaces
We present a novel hierarchical graphical model based contextaware hybr...
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Structured Adversarial Attack: Towards General Implementation and Better Interpretability
When generating adversarial examples to attack deep neural networks (DNN...
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Invariant Representations from Adversarially Censored Autoencoders
We combine conditional variational autoencoders (VAE) with adversarial c...
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Tversky as a Loss Function for Highly Unbalanced Image Segmentation using 3D Fully Convolutional Deep Networks
Fully convolutional deep neural networks have been asserted to be fast a...
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Realtime Deep Registration With Geodesic Loss
With an aim to increase the capture range and accelerate the performance...
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RealTime Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning
Brain segmentation is a fundamental first step in neuroimage analysis. I...
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Tversky loss function for image segmentation using 3D fully convolutional deep networks
Fully convolutional deep neural networks carry out excellent potential f...
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Autocontext Convolutional Neural Network (AutoNet) for Brain Extraction in Magnetic Resonance Imaging
Brain extraction or whole brain segmentation is an important first step ...
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Asymptotic Analysis of Objectives based on Fisher Information in Active Learning
Obtaining labels can be costly and timeconsuming. Active learning allow...
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Manifold unwrapping using density ridges
Research on manifold learning within a density ridge estimation framewor...
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