Title | ||
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Local Alignment Deep Network for Infrared-Visible Cross-Modal Person Reidentification in 6G-Enabled Internet of Things |
Abstract | ||
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In this article, we propose a novel deep framework termed local alignment deep network (LADN) for infrared-visible cross-modal person reidentification (IVCM ReID) in 6G-enabled IoT, which could meet the demands of all-day and real-time surveillance. The proposed LADN is designed as a two-stream structure, and it learns shallow interested feature maps and common subspace feature maps to reduce the ... |
Year | DOI | Venue |
---|---|---|
2021 | 10.1109/JIOT.2020.3038794 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
6G mobile communication,Internet of Things,Feature extraction,Streaming media,Smart devices,Real-time systems,Optical sensors | Journal | 8 |
Issue | ISSN | Citations |
20 | 2327-4662 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Shuang Liu | 1 | 36 | 22.95 |
Jingrui Zhang | 2 | 0 | 0.34 |