description [NeurIPS 2025][Segmentation][diffusion language model] By introducing convolutional decoding normalization (replacing hard semi-autoregressive chunking) and rule-based rejective ...
Abstract: This paper introduces a convolutional syndrome former (CSF) which enables reduced complexity decoding of regularly punctured convolutional codes (CCs) of rate r/(r + 1). The CSF is derived ...
ECoG signals are widely used in Brain-Computer Interfaces (BCIs) due to their high spatial resolution and superior signal quality, particularly in the field of neural control. ECoG enables more ...
Abstract: The channel mode of OCDMA system is interpreted first. Then a novel decoding of convolutional codes is proposed according to the characteristics of OCDMA system. And the feasibility of this ...
This is the official code repository for the paper: Fenglin Shi "MS-DBNet: a heterogeneous temporal convolutional network for robust subject-specific cross-session motor imagery decoding", Proc. SPIE ...
Researchers have demonstrated how to decode what the human brain is seeing by using artificial intelligence to interpret fMRI scans from people watching videos, representing a sort of mind-reading ...
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