基于深度注意力的融合全局和语义特征的图像描述模型OA

Aiming at the problems that existing image caption generation models face limitations when utilizing global features due to the fixed receptive field size,and object region-based image features lack background information,an image caption model(DFGS)is proposed.A multi-feature fusion module is designed to fuse global and semantic feature,allowing the model to focus on key object and background information in the image.A deep attention-based decoding module is designed to align visual and textual features,enhancing the generation of higher-quality image description statements.Experimental results on MSCOCO data-set show that the proposed model can produce more accurate captions,and is competitive compared with other advanced models.