Results 31 to 40 of about 572,458 (282)

Learning pronunciation dictionaries [PDF]

Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics -, 2006
The speed with which pronunciation dictionaries can be bootstrapped depends on the efficiency of learning algorithms and on the ordering of words presented to the user. This paper presents an active-learning word selection strategy that is mindful of human limitations. Learning rates approach that of an oracle system that knows the final LTS rule set.
John Kominek, Alan W Black
openaire   +1 more source

Single Image Super-Resolution Based on Deep Learning Features and Dictionary Model

IEEE Access, 2017
In traditional single image super-resolution (SR) methods based on dictionary model, a large number of image features are needed to train the SR dictionary.
Liling Zhao, Quansen Sun, Zelin Zhang
doaj   +1 more source

Compressed Online Dictionary Learning for Fast fMRI Decomposition [PDF]

, 2016
We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects. Introducing a
Mensch, Arthur, Thirion, Bertrand, Varoquaux, Gaël   +2 more
core   +5 more sources

Separable Dictionary Learning [PDF]

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
12 pages, 2 figures, 1 ...
Hawe, Simon, Seibert, Matthias, Kleinsteuber, Martin   +2 more
openaire   +2 more sources

A Novel Hyperspectral Endmember Extraction Algorithm Based on Online Robust Dictionary Learning

Remote Sensing, 2019
Due to the sparsity of hyperspectral images, the dictionary learning framework has been applied in hyperspectral endmember extraction. However, current endmember extraction methods based on dictionary learning are not robust enough in noisy environments.
Xiaorui Song, Lingda Wu
doaj   +1 more source

Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI

, 2014
We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRI) from highly undersampled k-space data. We perform dictionary learning as part of the image reconstruction process.
Ding, Xinghao, Fu, Xueyang, Huang, Yue, Lin, Qin, Paisley, John, Zhang, Xiao-ping   +5 more
core   +1 more source

Learning parametric dictionaries for graph signals [PDF]

, 2014
In sparse signal representation, the choice of a dictionary often involves a tradeoff between two desirable properties -- the ability to adapt to specific signal data and a fast implementation of the dictionary.
Frossard, Pascal, Shuman, David I, Thanou, Dorina   +2 more
core   +2 more sources

Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

Algorithms, 2017
We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online.
Xin Tian, Song Li
doaj   +1 more source

Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints

, 2015
Sparse representation models a signal as a linear combination of a small number of dictionary atoms. As a generative model, it requires the dictionary to be highly redundant in order to ensure both a stable high sparsity level and a low reconstruction ...
Nasrabadi, Nasser M., Sun, Xiaoxia, Tran, Trac D.   +2 more
core   +1 more source

Matrix of Polynomials Model based Polynomial Dictionary Learning Method for Acoustic Impulse Response Modeling [PDF]

, 2017
We study the problem of dictionary learning for signals that can be represented as polynomials or polynomial matrices, such as convolutive signals with time delays or acoustic impulse responses.
Dong, Jing, Feng, Pengming, Guan, Jian, Wang, Wenwu, Wang, Xuan   +4 more
core   +2 more sources