BSViT introduces burst spike coding and dual-channel attention into spiking vision transformers, improving accuracy over prior spiking transformers while preserving addition-only computation for neuromorphic hardware.
IEEE Transactions on Computer-aided Design of Integrated Circuits and Systems34(10), 1537–1557 (2015)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
BSViT: A Burst Spiking Vision Transformer for Expressive and Efficient Visual Representation Learning
BSViT introduces burst spike coding and dual-channel attention into spiking vision transformers, improving accuracy over prior spiking transformers while preserving addition-only computation for neuromorphic hardware.