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Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search
On the other hand, the similarity of cross-scale images is often smaller than that of images with the same scale for a person, which will increase the difficulty of matching.
Cross-media Scientific Research Achievements Query based on Ranking Learning
With the advent of the information age, the scale of data on the Internet is getting larger and larger, and it is full of text, images, videos, and other information.
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model
Science and technology big data contain a lot of cross-media information. There are images and texts in the scientific paper. The s ingle modal search method cannot well meet the needs of scientific researchers. This paper proposes a cross-media scientific research achievements retrieval method based on deep language model (CARDL). It achieves a unified cross-media semantic representation by learning the semantic association between different modal data, and is applied to the generation of text semantic vector of scientific research achievements, and then cross-media retrieval is realized through semantic similarity matching between different modal data. Experimental results show that the proposed CARDL method achieves better cross-modal retrieval performance than existing methods.
