3 papers
eess.SP2026
CG-MambaNet: A spatiotemporal framework for cross-patient epileptic seizure prediction using CNN-GCN-Mamba-BiLSTM with event-level clinical evaluation
Mufeng Chen, Qi Wu, Bingchao Huang +6
Epileptic seizure prediction from scalp EEG is critical for closed-loop neurostimulation therapy. Existing deep-learning methods share two architectural limitations: they model EEG…
eess.SP2026
CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention
Mufeng Chen, Qi Wu, Bingchao Huang +4
Reliable seizure prediction is a prerequisite for closed-loop neurostimulation therapy, yet existing methods rarely account for the variability in EEG signal quality encountered in…
cs.CV2025
Falcon: Fractional Alternating Cut with Overcoming Minima in Unsupervised Segmentation
Xiao Zhang, Xiangyu Han, Xiwen Lai +3
Today's unsupervised image segmentation algorithms often segment suboptimally. Modern graph-cut based approaches rely on high-dimensional attention maps from Transformer-based foun…