Jianan Li

S3GNet achieves unprecedented accuracy in hyperspectral salient object detection by effectively distinguishing between intrinsic material properties and misleading spectral variations.

Robots can autonomously discover and exploit geometric structures in their environment, leading to sophisticated collective behaviors from simple rewards.

FressDet achieves state-of-the-art multispectral object detection while using 93% fewer parameters, revolutionizing efficiency in the field.

Achieve faster, more accurate hyperspectral image classification by decoupling pixel clustering from classification, yielding region-level consistency and boundary alignment.