RadarSSM: A Lightweight Spatiotemporal State Space Network for Efficient Radar-Based Human Activity Recognition.
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| Title: | RadarSSM: A Lightweight Spatiotemporal State Space Network for Efficient Radar-Based Human Activity Recognition. |
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| Authors: | Zhao R; College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China., Miao F; Graduate School of Science and Technology, Shinshu University, Nagano 390-8621, Japan., Liu Y; College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China. |
| Source: | Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Apr 06; Vol. 26 (7). Date of Electronic Publication: 2026 Apr 06. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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