Index for elad

Elad, A.[Asi] * 2001: Bending Invariant Representations for Surfaces
* 2003: On bending invariant signatures for surfaces
* 2005: Texture Mapping via Spherical Multi-dimensional Scaling
* 2007: Low Bit-Rate Compression of Facial Images
* 2019: Direct Validation of the Information Bottleneck Principle for Deep Nets
Includes: Elad, A.[Asi] Elad, A.

Elad, M.[Michael] * 1997: Restoration of a Single Superresolution Image from Several Blurred, Noisy, and Undersampled Measured Images
* 1998: Recursive Optical Flow Estimation: Adaptive Filtering Approach
* 1999: Optimal Filters for Gradient-based Motion Estimation
* 1999: Super-resolution Reconstruction of Continuous Image Sequences
* 1999: Super-Resolution Reconstruction of Image Sequences
* 1999: Superresolution Restoration of an Image Sequence: Adaptive Filtering Approach
* 2001: Down-scaling for better transform compression
* 2001: fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur, A
* 2001: On Sparse Signal Representations
* 2001: Pattern Detection Using a Maximal Rejection Classifier
* 2002: Generalized Uncertainty Principle and Sparse Representation in Pairs of Bases, A
* 2002: On the origin of the bilateral filter and ways to improve it
* 2002: Rejection based classifier for face detection
* 2003: Down-scaling for better transform compression
* 2003: Fast and Robust Super-Resolution
* 2003: Optimal framework for low bit-rate block coders
* 2003: Reduced complexity Retinex algorithm via the variational approach
* 2003: Variational Framework for Retinex, A
* 2004: Advances and challenges in super-resolution
* 2004: Fast and Robust Multiframe Super Resolution
* 2005: Image decomposition via the combination of sparse representations and a variational approach
* 2005: On the Design of Filters for Gradient-Based Motion Estimation
* 2005: Pixels that Sound
* 2005: Retinex by Two Bilateral Filters
* 2005: Space-Dependent Color Gamut Mapping: A Variational Approach
* 2005: Variable Projection for Near-Optimal Filtering in Low Bit-Rate Block Coders
* 2006: Image Denoising Via Learned Dictionaries and Sparse representation
* 2006: Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
* 2006: Image Denoising with Shrinkage and Redundant Representations
* 2006: K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
* 2006: Multiframe Demosaicing and Super-Resolution of Color Images
* 2006: Video-to-Video Dynamic Super-Resolution for Grayscale and Color Sequences
* 2007: Biblio: Automatic Meta-Data Extraction
* 2007: Multiscale Sparse Image Representation with Learned Dictionaries
* 2008: Compression of facial images using the K-SVD algorithm
* 2008: Sparse And Redundant Modeling Of Image Content Using An Image-Signature-Dictionary
* 2008: Sparse Representation for Color Image Restoration
* 2009: Generalizing the Nonlocal-Means to Super-Resolution Reconstruction
* 2009: Image Sequence Denoising via Sparse and Redundant Representations
* 2009: Super Resolution With Probabilistic Motion Estimation
* 2009: Super-Resolution Without Explicit Subpixel Motion Estimation
* 2010: Applications of Sparse Representation and Compressive Sensing
* 2010: Dictionaries for Sparse Representation Modeling
* 2010: L1-L2 Optimization in Signal and Image Processing
* 2010: On the Role of Sparse and Redundant Representations in Image Processing
* 2010: Shrinkage Learning Approach for Single Image Super-Resolution with Overcomplete Representations, A
* 2010: Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing
* 2012: Example-based cross-modal denoising
* 2012: Redundant Wavelets on Graphs and High Dimensional Data Clouds
* 2012: Sparse and Redundant Representation Modeling: What Next?
* 2013: Image Processing Using Smooth Ordering of its Patches
* 2013: Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse
* 2013: Improving K-SVD denoising by post-processing its method-noise
* 2013: Probabilistic Subspace Clustering Via Sparse Representations
* 2014: Facial Image Compression using Patch-Ordering-Based Adaptive Wavelet Transform
* 2014: Image denoising through multi-scale learnt dictionaries
* 2014: Patch-Ordering-Based Wavelet Frame and Its Use in Inverse Problems
* 2014: Single Image Interpolation Via Adaptive Nonlocal Sparsity-Based Modeling
* 2014: Sparsity based poisson inpainting
* 2014: Sparsity-Based Poisson Denoising With Dictionary Learning
* 2014: Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution, A
* 2015: Bi-l0-l2-norm regularization for blind motion deblurring
* 2015: Boosting of Image Denoising Algorithms
* 2015: Expected Patch Log Likelihood with a Sparse Prior
* 2015: Guest Editorial: Sparse Coding
* 2015: Sparsity Based Methods for Overparameterized Variational Problems
* 2015: Spatially-Adaptive Reconstruction in Computed Tomography Using Neural Networks
* 2016: Con-Patch: When a Patch Meets Its Context
* 2016: Large Inpainting of Face Images With Trainlets
* 2016: Multi-Scale Patch-Based Image Restoration
* 2016: Patch Ordering as a Regularization for Inverse Problems in Image Processing
* 2016: Poisson inverse problems by the Plug-and-Play scheme
* 2016: Postprocessing of Compressed Images via Sequential Denoising
* 2016: Turning a denoiser into a super-resolver using plug and play priors
* 2017: Convolutional Dictionary Learning via Local Processing
* 2017: Little Engine That Could: Regularization by Denoising (RED), The
* 2017: Style Transfer Via Texture Synthesis
* 2018: Compression for Multiple Reconstructions
* 2018: Example-Based Image Synthesis via Randomized Patch-Matching
* 2018: Optimized Pre-Compensating Compression
* 2019: Acceleration of RED via vector extrapolation
* 2019: Local Block Coordinate Descent Algorithm for the CSC Model, A
* 2019: Unified Single-Image and Video Super-Resolution via Denoising Algorithms
* 2020: Adversarial Noise Attacks of Deep Learning Architectures: Stability Analysis via Sparse-Modeled Signals
* 2020: LIDIA: Lightweight Learned Image Denoising with Instance Adaptation
* 2020: On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks
* 2020: Unsupervised Single Image Dehazing Using Dark Channel Prior Loss
* 2021: Better Compression With Deep Pre-Editing
* 2021: Deep K-SVD Denoising
* 2021: Learned Greedy Method (LGM): A novel neural architecture for sparse coding and beyond
* 2021: Regularization by Denoising via Fixed-Point Projection (RED-PRO)
Includes: Elad, M.[Michael] Elad, M.
91 for Elad, M.

Eladawi, N. * 2018: Early Diagnosis of Diabetic Retinopathy in OCTA Images Based on Local Analysis of Retinal Blood Vessels and Foveal Avascular Zone
* 2019: Early Signs Detection of Diabetic Retinopathy Using Optical Coherence Tomography Angiography Scans Based on 3D Multi-Path Convolutional Neural Network

Eladawy, A.[Ahmed] * 2021: Remotely Sensed Ecological Protection Redline and Security Pattern Construction: A Comparative Analysis of Pingtan (China) and Durban (South Afric

Eladhari, M.P. * 2014: Mind Module: Using an Affectand Personality Computational Modelas a Game-Play Element, The

Index for "e"


Last update:20-Oct-21 11:39:35
Use price@usc.edu for comments.