Depeng Liang

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In this paper we propose a novel hierarchical feature composition and selection model used in facial age estimation. In recent years, hierarchical architectures have been shown to outperform the flat structure on a variety of visual modeling tasks and has drawn a lot of attention. In our hierarchical architecture, we use biological inspired features as(More)
Regression testing involves testing not only the functionality containing a defect but also testing related functionality to check if a change has introduce side effects. In order to check for the above, a change impact model has been developed using the artifacts built for the software during the design phase. Using both static and dynamic diagrams of UML,(More)
Recently deeplearning models have been shown to be capable of making remarkable performance in sentences and documents classification tasks. In this work, we propose a novel framework called ACBLSTM for modeling setences and documents, which combines the asymmetric convolution neural network (ACNN) with the Bidirectional Long ShortTerm Memory network(More)
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