Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

The perception of the surrounding environment is a key requirement for autonomous driving
systems, yet the computation of an accurate semantic representation of the scene starting …

This paper proposes an efficient optimization algorithm based on the physical phenomenon
of rime-ice, called the RIME. The RIME algorithm implements the exploration and …

Multi-modality image fusion and segmentation play a vital role in autonomous driving and
robotic operation. Early efforts focus on boosting the performance for only one task, eg …

In recent years, remote-sensing scene classification is one of the research hotspots and has
played an important role in the field of intelligent interpretation of remote-sensing data …

Scene understanding based on image segmentation is a crucial component of autonomous
vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting …

Most recent methods for RGB (red–green–blue)-thermal salient object detection (SOD)
involve several floating-point operations and have numerous parameters, resulting in slow …

Image fusion aims to integrate complementary characteristics of source images into a single
fused image that better serves human visual observation and machine vision perception …

Multimodal fusion can make semantic segmentation more robust. However, fusing an
arbitrary number of modalities remains underexplored. To delve into this problem, we create …

In recent years, various neural network architectures for computer vision have been devised,
such as the visual transformer and multilayer perceptron (MLP). A transformer based on an …