In this paper we introduce a sparse kernel learning framework for the Continuous Relevance Model (CRM). State-of-the-art image annotation models linearly ...

ABSTRACT. In this paper we introduce a sparse kernel learning frame- work for the Continuous Relevance Model (CRM). State-of- the-art image annotation ...

In this paper we introduce a sparse kernel learning frame- work for the Continuous Relevance Model (CRM). State-of- the-art image annotation models linearly ...

A sparse kernel learning framework for the Continuous Relevance Model (CRM) that greedily selects an optimal combination of kernels, which rapidly converges ...

In this paper we introduce a sparse kernel learning framework for the Continuous Relevance Model (CRM). State-of-the-art image annotation models linearly ...

This paper leverages a self-explanatory re- formulation of sparse representation, i.e., linking the learned dictionary atoms with the original feature spaces ...

In this paper, we propose a novel local sparse model for multi-label image annotation. Existing feature descriptors and extraction algorithms pay less attention ...

Nov 6, 2018 · Bibliographic details on Sparse Kernel Learning for Image Annotation.

Apr 2, 2014 · The document describes an approach called Sparse Kernel Continuous Relevance Model (SKL-CRM) for image annotation.

Jul 16, 2018 · We propose a new convolutional sparse kernel network (CSKN), which is a hierarchical unsupervised feature learning framework that addresses the ...