IEEE

Enhancing SEEG-Based Speech Decoding via Convolutional Encoder-Decoder and Scale-Recursive Reconstructor

Abstract: A brain-computer interface (BCI) that decodes speech directly from neural activity provides a rapid and natural means of communication for individuals with speech impairments or aphasia.

Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan ...
IEEE

Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention

Abstract: Segmenting biomarkers in medical images is crucial for various biotech applications. Despite advances, Transformer and CNN based methods often struggle with variations in staining and ...