Professor Nan Ma of Beijing University of Technology and her research team published a paper titled “Interactive Cognition of Self-driving: A Multi-dimensional Analysis Model and Implementation” in the 2025 issue of Research. We introduce the significance of research in the field of self-driving interactive cognition, detailing its components and underlying infrastructure.

Forests and plantations play a vital role in carbon sequestration, yet accurately monitoring their growth remains costly and labor-intensive. 

A new study introduces ACA-SIM (atmospheric correction based on satellite–in situ matchup data), a neural-network-based atmospheric correction algorithm that uses real satellite–Aerosol Robotic Network-Ocean Color (AERONET-OC) matchups to improve the accuracy of atmospheric correction over coastal waters. 

Accurate classification of wetland vegetation is essential for biodiversity conservation and carbon cycle monitoring. 

A team led by Prof. Fei Ling from South China University of Technology developed PRTS (Pathology-driven Reconstruction of Transcriptomic States), a deep learning framework that predicts single-cell-resolution spatial transcriptomics directly from H&E-stained histology images.