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Generalized Tensor-based Multiple Feature Fusion Network using Block Decomposition
In this paper, we propose a multiple feature fusion method using tensor Block decomposition. Theoretically, it is a general form of two previous tensor decomposition approaches and holds strengths from both of them. Based on the Block decomposition, we construct the corresponding Multiple feature Block Fusion Network (MBFN) practically. Our MBFN is applicable to both unimodal features and multimodal features and it can fuse multiple features at the same time.
Jiaru Zhang, Yang Hua, Zhengui Xue, Tao Song, Ruhui Ma, Haibing Guan
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Generalized Tensor-based Multiple Feature Fusion Network using Block Decomposition