Task-specific data-fusion networks have marked considerable achievements in urban scene
parsing. Among these networks, our recently proposed RoadFormer successfully extracts …

Semantic segmentation and stereo matching are two essential components of 3D
environmental perception systems for autonomous driving. Nevertheless, conventional …

Unsupervised monocular depth estimation frameworks have shown promising performance
in autonomous driving. However, existing solutions primarily rely on a simple convolutional …

Recognition of passable areas of mine roads based on vehicle perspective is crucial for
autonomous vehicles to drive in unmanned open-pit mine scenes. In the past few years …

In the emerging field of urban digital twins (UDTs), there are extensive and captivating
opportunities for leveraging cutting-edge deep learning techniques. Particularly within the …

Data-fusion networks have shown significant promise for RGB-thermal scene parsing.
However, the majority of existing studies have relied on symmetric duplex encoders for …

This article introduces three-filters-to-normal (3F2N), an extension of our previous work three-
filters-to-normal (3F2N), with a specific focus on incorporating discontinuity discrimination …

Optic nerve head (ONH) detection has been a crucial area of study in ophthalmology for
years. However, the significant discrepancy between fundus image datasets, each …

Feature-fusion networks with duplex encoders have proven to be an effective technique to
solve the freespace detection problem. However, despite the compelling results achieved by …

Over the past decade, automated methods have been developed to detect cracks more
efficiently, accurately, and objectively, with the ultimate goal of replacing conventional …