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Text-based image retrieval system using semantic visual content for re-ranking
DOI:10.1016/j.engappai.2025.111770.png)
Abstract
En 中文
• Overview of the workings of a commercial image retrieval system, filling a gap in existing literature. • Text-based retrieval is significantly improved using content analysis via deep image embeddings. • Filtering irrelevant images is possible by clustering candidate images based on embeddings. • Re-ranking is possible based on the novel idea of a “master image” of a query.
Keywords:
image retrieval
deep image embeddings
clustering
re-ranking
master image
Journal
IF:
8
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5.4K
Citations:
3.5W

