DSINet uses a selective spatial state unit (S3U) from Mamba and concentration-balanced distillation (CBD) to keep spatial change representations stable across incremental domains while preserving linear efficiency.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing16, 3867–3878 (2023)
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A two-level overlapping Schwarz domain decomposition constructs a hierarchical attention operator that trains faster and approximates the inverse of a discretized 1D diffusion operator more accurately than global low-rank attention while using fewer parameters.
citing papers explorer
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Dual-Selective Network for Domain-Incremental Change Detection
DSINet uses a selective spatial state unit (S3U) from Mamba and concentration-balanced distillation (CBD) to keep spatial change representations stable across incremental domains while preserving linear efficiency.
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Hierarchical Attention via Domain Decomposition
A two-level overlapping Schwarz domain decomposition constructs a hierarchical attention operator that trains faster and approximates the inverse of a discretized 1D diffusion operator more accurately than global low-rank attention while using fewer parameters.