Leiquan Wang

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Cross modal (e.g., text-to-image or image-to-text) retrieval has received great attention with the flushed multi-modal social media data. It is of considerable challenge to stride across the heterogeneous gap between modalities. Existing methods project different modalities into a common space by minimizing the distance within the heterogeneous pairs(More)
For the purpose of enhancing discriminability of convolutional neural networks (CNNs) and facilitating optimization, a multilayer structured variant of the maxout unit (named Multilayer Maxout Network, MMN) is proposed in this paper. CNNs with maxout units employ linear convolution filters followed by maxout units to abstract representations from less(More)
In social image search, most existing hypergraph methods use the visual and textual features in isolation by treating each feature term as a hyperedge. Nevertheless, they neglect the correlations of visual and textual hyperedges, which are more robust to represent the high-order relationship among vertices. In this paper, we propose a hypergraph with(More)
Phellinus is a kind of fungus and known as one of the elemental components in drugs to avoid cancer. With the purpose of finding optimized culture conditions for Phellinus production in the lab, plenty of experiments focusing on single factor were operated and large scale of experimental data was generated. In previous work, we used regression analysis and(More)
Welan gum is a kind of novel microbial polysaccharide, which is widely produced during the process of microbial growth and metabolism in different external conditions. Welan gum can be used as the thickener, suspending agent, emulsifier, stabilizer, lubricant, film-forming agent and adhesive usage in agriculture. In recent years, finding optimal(More)
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