We developed a new reasoning-driven segmentation framework for remote sensing that bridges abstract semantic understanding and precise pixel-level delineation.
We developed digital visual-motor systems and algorithms to autonomously evaluate developmental coordination disorder (DCD) and delve into associated pathologies.
We developed deep learning methods to automatically discover action segments from the untrimmed videos.
We are developing SDF-based AI models for computational electromagnetics.
We are developing AI models for computational electromagnetics.
From brain-in-the-loop to brain-out-of-the-loop
We developed a prior-guided framework for RSVP-EEG decoding and found that, for this task, a simple MLP can match or even outperform Transformer-based models.
We proposed a brain-machine fusion approach to achieve the brain-in-the-loop modeling and brain-out-of-the-loop application.
Boosting brain-computer interface performance through cognitive training: a brain-centric approach
We developed deep learning methods for quantitative muscle atrophy evaluation using ultrasound images.
