iSPEED: a Scalable and Distributed In-Memory Based Spatial Query System for Large and Structurally Complex 3D Data
Summary: iSPEED is a scalable, distributed in-memory spatial query system for massive, complex 3D pathology data. It uses progressive compression with multi-level detail, in-memory/global indexes plus on-demand indexing, and structural indexing to speed 3D joins, nearest neighbor, and proximity queries via REST. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Hoang Vo
- 2. Yanhui Liang
- 3. Jun Kong
- 4. Fusheng Wang
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,126 | High-Performance Spatial Data Analytics: Systematic R&D for Scale-Out and Scale-Up Solutions from the Past to Now | 2024 | VLDB | 4.1945683e-05 |
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