A Cross-Modal Sentiment Classification Method Based on Compact Bilinear Fusion of Image and Text
An emotion classification and bilinear technology, applied in text database clustering/classification, character and pattern recognition, unstructured text data retrieval, etc., can solve problems such as cross-modal emotion classification of images and texts, and achieve good images Effects of Emotional Traits
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[0033] Such as figure 1 Shown is the overall structure diagram of the present invention. exist figure 1Among them, the pre-trained 152-layer residual network is used to extract the feature representation of the image, and the two-layer LSTM model is used to extract the feature representation of the text, and then the two features are stitched together, and the soft attention map is generated through two layers of convolutional layers and softmax. The product of the corresponding position of the soft attention map and the image feature representation is summed to obtain the attention feature representation of the image, then the MCB algorithm is used to fuse the image attention feature representation and the text feature representation, and finally the softmax classifier is used to complete the cross-modality of the image and text Sentiment classification.
[0034] Such as figure 2 Shown is the MCB fusion algorithm model diagram of the present invention. This figure illu...
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