Unsupervised learning of compositional sparse code for natural image representation

DOI10.1090/S0033-569X-2013-01361-5zbMath1415.94025OpenAlexW2077669678WikidataQ114896925 ScholiaQ114896925MaRDI QIDQ5420097

Zhangzhang Si, Ying Nian Wu, Song-Chun Zhu, Yi Hong, Wenze Hu

Publication date: 11 June 2014

Published in: Quarterly of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1090/s0033-569x-2013-01361-5

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (2)

Learning sparse FRAME models for natural image patterns ⋮ A tale of three probabilistic families: Discriminative, descriptive, and generative models

Uses Software

• LIBSVM
• LIBLINEAR
• PDCO
• SIFT

Cites Work

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• Algorithms for simultaneous sparse approximation. I: Greedy pursuit
• Estimating the dimension of a model
• Support union recovery in high-dimensional multivariate regression
• Mathematical classification and clustering
• From information scaling of natural images to regimes of statistical models
• Exploratory Projection Pursuit
• Atomic Decomposition by Basis Pursuit
• Composition systems
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Uncertainty principles and ideal atomic decomposition
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Matching pursuits with time-frequency dictionaries
• Model Selection and Estimation in Regression with Grouped Variables

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