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Does the sparse feature encoder contribute to recognition?
In this paper we propose a novel sparse feature selection framework for web image annotation, namely sparse Feature Selection based on Graph Laplacian (FSLG 2.
Sparse feature selection has proven to be effective in analyzing high-dimensional data.
We plan to solve this limitation by replacing hand-designed features with sparse feature learning.
However, AODV may fail frequently due to the sparse feature of a vehicular network.
Since P l >1, the model learns overcomplete sparse, feature feature maps.
Similar(11)
Since the high-frequency NSCT coefficients have the sparse features, after being sparsely represented again by wavelet transform, their sparsity is enhanced.
Sparse feature-matching and image-to-image matching procedures (Forsyth and Ponce 2003; Brown and Lowe 2007) are used to estimate the camera motion incrementally.
The CMS is based on variation of sparse features set.
We learn sparse features from the preprocessed data described above.
Based on clustering analysis of multi-domain sparse features extracted, the localized faults are successfully identified.
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