Add to ORKGInternational audienceThis paper presents a multi-layer dictionary learning method for classification tasks. The goal of the proposed multi-layer framework is to use the supervised dictionary learning approach locally on raw images in order to learn local features. This method starts by building a sparse representation at the patch-level and relies on a hierarchy of learned dictionaries to output a global sparse representation for the whole image. It relies on a succession of sparse coding and pooling steps in order to find an efficient representation of the data for classification. This method has been tested on a classification task with good results
Recently, dictionary learned by sparse coding has been widely adopted in image classification and ha...
© 2014 IEEE. Dictionary learning (DL) for sparse coding has shown promising results in classificatio...
Le domaine de l'apprentissage de dictionnaire est le sujet d'attentions croissantes durant cette der...
Ces dernières années, de nombreux travaux ont été publiés sur l'encodage parcimonieux et l'apprentis...
International audienceThis paper presents a descriptor extraction method in the context of image cla...
The sparse coding technique has shown flexibility and capability in image representation and analysi...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
Yang M., Dai D., Shen L., Van Gool L., ''Latent dictionary learning for sparse representation based ...
In this paper, we aim to extend dictionary learning onto hierarchical image representations in a pri...
Abstract — Dictionary learning algorithms have been success-fully used for both reconstructive and d...
This paper seeks to combine dictionary learning and hierarchical image representation in a principle...
Classifiers based on sparse representations have recently been shown to provide excellent results in...
The employed dictionary plays an important role in sparse representation or sparse coding based imag...
Recently, dictionary learned by sparse coding has been widely adopted in image classification and ha...
© 2014 IEEE. Dictionary learning (DL) for sparse coding has shown promising results in classificatio...
Le domaine de l'apprentissage de dictionnaire est le sujet d'attentions croissantes durant cette der...
Ces dernières années, de nombreux travaux ont été publiés sur l'encodage parcimonieux et l'apprentis...
International audienceThis paper presents a descriptor extraction method in the context of image cla...
The sparse coding technique has shown flexibility and capability in image representation and analysi...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
In the recent years, numerous works have been published on dictionary learning and sparse coding. Th...
Yang M., Dai D., Shen L., Van Gool L., ''Latent dictionary learning for sparse representation based ...
In this paper, we aim to extend dictionary learning onto hierarchical image representations in a pri...
Abstract — Dictionary learning algorithms have been success-fully used for both reconstructive and d...
This paper seeks to combine dictionary learning and hierarchical image representation in a principle...
Classifiers based on sparse representations have recently been shown to provide excellent results in...
The employed dictionary plays an important role in sparse representation or sparse coding based imag...
Recently, dictionary learned by sparse coding has been widely adopted in image classification and ha...
© 2014 IEEE. Dictionary learning (DL) for sparse coding has shown promising results in classificatio...
Le domaine de l'apprentissage de dictionnaire est le sujet d'attentions croissantes durant cette der...