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Xiqing Guo

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Open access 2026

SenSNN: Energy-Efficient Tiny-Object Pseudo-Mask Segmentation via a Dual-Stream Membrane Shortcut

Results indicate that SenSNN provides a complementary low-energy architecture for dense tiny-object screening under constrained operation-level energy budgets, and shows that localized spiking consensus provides a more efficient tradeoff than global attention for subpixel targets.

Runxiang Wang, Hao Li, Xiqing Guo · 0 citations