942 citations · 2.3k across the 50 of their papers we have counts for
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Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation
Miguel Monteiro, Mário A. T. Figueiredo, Arlindo L. Oliveira
The Conditional Random Field as a Recurrent Neural Network layer is a recently proposed algorithm meant to be placed on top of an existing Fully-Convolutional Neural Network to imp…
Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF). Unlike related models based on Markov Random Fields (MR…
External Patch-Based Image Restoration Using Importance Sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper introduces a new approach to patch-based image restoration based on external datasets and importance sampling. The Minimum Mean Squared Error (MMSE) estimate of the imag…
Impulsive Noise Robust Sparse Recovery via Continuous Mixed Norm
Amirhossein Javaheri, Hadi Zayyani, Mario A. T. Figueiredo +1
This paper investigates the problem of sparse signal recovery in the presence of additive impulsive noise. The heavytailed impulsive noise is well modelled with stable distribution…
Poisson Image Denoising Using Best Linear Prediction: A Post-processing Framework
Milad Niknejad, Mario A. T. Figueiredo
In this paper, we address the problem of denoising images degraded by Poisson noise. We propose a new patch-based approach based on best linear prediction to estimate the underlyin…
Scene-Adapted Plug-and-Play Algorithm with Guaranteed Convergence: Applications to Data Fusion in Imaging
Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
The recently proposed plug-and-play (PnP) framework allows leveraging recent developments in image denoising to tackle other, more involved, imaging inverse problems. In a PnP meth…