Nature

RFGLNet for adverse weather domain-generalized semantic segmentation with frequency low-rank enhancement

Semantic segmentation in adverse weather conditions presents significant challenges due to insufficient image brightness, excessive noise, and blurred object boundaries, which hinder the performance ...
Nature

A deep learning method for optimizing semantic segmentation accuracy of remote sensing images based on improved UNet

Semantic segmentation of remote sensing imagery (RSI) is critical in many domains due to the diverse landscapes and different sizes of geo-objects that RSI contains, making semantic segmentation ...
DLR

DLR-SkyScapes: Aerial Semantic Segmentation Dataset for HD-mapping

High-Definition(HD) mapping is in many applications from autonomous driving to infrastructure monitoring, and urban management essential for the understanding of complex urban infrastructure with ...

DGIST-MIT Research Team Wins First Place at Global Robot Vision Challenge, Demonstrates Unstructured Environment Recognition Technology

A joint research team from Daegu Gyeongbuk Institute of Science and Technology (DGIST) and the Massachusetts Institute of ...
The Chosun Ilbo on MSN

DGIST-MIT team tops AI autonomous driving challenge

A joint research team from Daegu Gyeongbuk Institute of Science and Technology (DGIST) and the Massachusetts Institute of Technology (MIT) in the U.S. won first place in an international competition ...