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arXiv · 1703.03957

Neural method for Explicit Mapping of Quasi-curvature Locally Linear Embedding in image retrieval

Shenglan Liu·Jun Wu·Lin Feng·Feilong Wang
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Abstract

This paper proposed a new explicit nonlinear dimensionality reduction using neural networks for image retrieval tasks. We first proposed a Quasi-curvature Locally Linear Embedding (QLLE) for training set. QLLE guarantees the linear criterion in neighborhood of each sample. Then, a neural method (NM) is proposed for out-of-sample problem. Combining QLLE and NM, we provide a explicit nonlinear dimensionality reduction approach for efficient image retrieval. The experimental results in three benchmark datasets illustrate that our method can get better performance than other state-of-the-art out-of-sample methods.

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Shenglan Liu, Jun Wu, Lin Feng, Feilong Wang. 2017-03-11. Neural method for Explicit Mapping of Quasi-curvature Locally Linear Embedding in image retrieval. https://arxiv.org/abs/1703.03957

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