HISA: A Query System Bridging The Semantic Gap For Large Image Databases
Summary: HISA is a query system for image collections, introducing the first data structure that captures both ontological knowledge and visual features for retrieval by keywords or image examples. Annotation and statistics pre-compute the structure to bridge semantics and visuals, enabling fast queries. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Gang Chen
- 2. Xiaoyan Li
- 3. Lidan Shou
- 4. Jinxiang Dong
- 5. Chun Chen
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 79 | A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces | 1998 | VLDB | 0.00056242144 |
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