
Weaklysupervised Highresolution Segmentation of Mammography Images for Breast Cancer Diagnosis
In the last few years, deep learning classifiers have shown promising re...
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Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
Normalization techniques have become a basic component in modern convolu...
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Unsupervised Deep Video Denoising
Deep convolutional neural networks (CNNs) currently achieve stateofthe...
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Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy
Denoising is a fundamental challenge in scientific imaging. Deep convolu...
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An artificial intelligence system for predicting the deterioration of COVID19 patients in the emergency department
During the COVID19 pandemic, rapid and accurate triage of patients at t...
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EarlyLearning Regularization Prevents Memorization of Noisy Labels
We propose a novel framework to perform classification via deep learning...
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Towards datadriven stroke rehabilitation via wearable sensors and deep learning
Recovery after stroke is often incomplete, but rehabilitation training m...
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A Sampling Theorem for Deconvolution in Two Dimensions
This work studies the problem of estimating a twodimensional superposit...
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Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization
Extraneous variables are variables that are irrelevant for a certain tas...
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On the design of convolutional neural networks for automatic detection of Alzheimer's disease
Early detection is a crucial goal in the study of Alzheimer's Disease (A...
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Robust and interpretable blind image denoising via biasfree convolutional neural networks
Deep convolutional networks often append additive constant ("bias") term...
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Datadriven Estimation of Sinusoid Frequencies
Frequency estimation is a fundamental problem in signal processing, with...
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Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
Extracting information from nonlinear measurements is a fundamental chal...
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TimeSeries Analysis via LowRank Matrix Factorization: Applied to InfantSleep Data
We propose a nonparametric model for time series with missing data based...
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A LearningBased Framework for LineSpectra Superresolution
We propose a learningbased approach for estimating the spectrum of a mu...
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Multicompartment Magnetic Resonance Fingerprinting
Magnetic resonance fingerprinting (MRF) is a technique for quantitative ...
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Carlos FernandezGranda
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