Research on Image and Text Retrieval Model Utilizing Hierarchical Clustering
The application and impact of image-text retrieval in industry are multifaceted,as it can help improve research and de-velopment efficiency,promote technological innovation,and enhance product quality and competitiveness.Currently,the emphasis of image-text retrieval models is on improving retrieval accuracy.With the rapid development of technology and data,the continuous ap-plication of deep learning and large-scale model techniques has gradually highlighted the issue of retrieval speed in image-text retrieval.To address the current limitations in retrieval speed and high computational requirements,a hierarchical clustering-based image-text retrieval model has been proposed.This method adopts a cross-modal hashing approach with evident retrieval effectiveness and applies deep clustering algorithms to classify the data to be retrieved,thereby reducing the retrieval scope and improving retrieval speed.Ex-perimental results indicate that the hierarchical clustering-based image-text retrieval model significantly enhances retrieval speed while maintaining retrieval accuracy,enabling engineering personnel to obtain satisfactory retrieval results more quickly.
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