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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)
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 AC-BLSTM for modeling setences and documents, which combines the asymmetric convolution neural network (ACNN) with the Bidirectional Long Short-Term Memory network(More)
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