Skip to main navigation
Skip to search
Skip to main content
Tel Aviv University Home
Update Request & User Guide (TAU staff only)
Home
Experts
Research units
Research output
Datasets
Prizes
Activities
Courses
Press/Media
Search by expertise, name or affiliation
A greedy approach to ℓ
0,
ω
-based convolutional sparse coding
Elad Plaut,
Raja Giryes
School of Electrical Engineering
Tel Aviv University
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A greedy approach to ℓ
0,
ω
-based convolutional sparse coding'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Sparsity
100%
Greedy Approach
100%
Convolutional Sparse Coding
100%
Sparse Coding
100%
Optimization Problem
50%
Image Processing
50%
Reconstructed Image
50%
Encoding Method
50%
Non-convexity
50%
Whole Image
50%
L1-norm
50%
Greedy Method
50%
Image Inpainting
50%
Dictionary Learning
50%
Pursuit Algorithm
50%
Shift-invariant Dictionary
50%
Convex Relaxation
50%
Coding Learning
50%
Sparse Dictionary
50%
Noisy Image
50%
Matching Pursuit
50%
Sparsity Prior
50%
Overlapping Patches
50%
Salt-and-pepper Noise Removal
50%
Engineering
Greedy Approach
100%
Sparse Coding
100%
Sparsity
75%
Image Processing
25%
Optimisation Problem
25%
Reconstructed Image
25%
Image Inpainting
25%
Invariant Dictionary
25%
Pursuit Algorithm
25%
Recovered Image
25%
Dictionary Learning
25%
Matching Pursuit
25%
Pepper Noise
25%
Computer Science
Sparsity
100%
Optimization Problem
33%
Coding Technique
33%
Dictionary Learning
33%
Pursuit Algorithm
33%
Matching Pursuit
33%
Image Processing
33%
Image Inpainting
33%
Convex Relaxation
33%
Reconstructed Image
33%
Invariant Dictionary
33%
Recovered Image
33%
Neuroscience
Face
100%
Image Processing
100%
Immunology and Microbiology
Face
100%