Real-time semantic segmentation is a crucial component of autonomous driving systems,
where accurate and efficient scene interpretation is essential to ensure both safety and …

Automatic road extraction from remote sensing images has an important impact on road
maintenance and land management. While significant deep-learning-based approaches …

Current semantic segmentation methods have high accuracy. However, it has the
disadvantage of high computational complexity and time consumption, which makes it …

Deploying efficient and fast semantic segmentation networks on edge computing platforms
in real-world environments is desired and challenging. To address this challenge, we …

This letter presents an innovative approach for generating pixel-wise pseudo masks as
supervision for image-level Weakly Supervised Semantic Segmentation (WSSS). This is …

Accurate segmentation of safe navigable areas is crucial for scene parsing in autonomous
driving systems. However, existing segmentation methods often fail to fully leverage the …

In the semantic segmentation field, the dual-branch structure is a highly effective
segmentation model. However, the frequent downsampling in the semantic branch reduces …

Segmentation of safe navigable areas is a crucial technology for scene parsing in autopilot
systems. However, existing segmentation methods often fail to adequately exploit the …

With the increasing application of embedded mobile devices in various fields, lightweight
real-time semantic segmentation systems have attracted more and more attention. Many …

The current mainstream image semantic segmentation networks often suffer from mis-
segmentation, segmentation discontinuity, and high model complexity, which limit their …