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    ARTICLE

    Improved Blending Attention Mechanism in Visual Question Answering

    Siyu Lu1, Yueming Ding1, Zhengtong Yin2, Mingzhe Liu3,*, Xuan Liu4, Wenfeng Zheng1,*, Lirong Yin5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1149-1161, 2023, DOI:10.32604/csse.2023.038598

    Abstract Visual question answering (VQA) has attracted more and more attention in computer vision and natural language processing. Scholars are committed to studying how to better integrate image features and text features to achieve better results in VQA tasks. Analysis of all features may cause information redundancy and heavy computational burden. Attention mechanism is a wise way to solve this problem. However, using single attention mechanism may cause incomplete concern of features. This paper improves the attention mechanism method and proposes a hybrid attention mechanism that combines the spatial attention mechanism method and the channel attention mechanism method. In the case… More >

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