Environmental perception technology is the guarantee of the safety of driverless vehicles. At
present, there are a lot of researches and reviews on environmental perception, aiming to …

To improve the performance of salient object detection (SOD) in scenes with low-light
conditions (eg, nighttime) and cluttered backgrounds, infrared thermal images are used to …

In recent years, how to strike a good trade-off between accuracy, inference speed, and
model size has become the core issue for real-time semantic segmentation applications …

Real-time semantic segmentation, which can be visually understood as the pixel-level
classification task on the input image, currently has broad application prospects, especially …

In the past decade, convolutional neural networks (CNNs) have shown prominence for
semantic segmentation. Although CNN models have very impressive performance, the …

Both Convolutional Neural Networks (CNNs) and Transformers have shown great success
in semantic segmentation tasks. Efforts have been made to integrate CNNs with Transformer …

Real-time running deep convolutional neural networks on embedded electronics is one
recent focus for distracted driving detection. In this work, we proposed, which is a unique …

Alzheimer's disease (AD) is an irreversible central nervous degenerative disease, while mild
cognitive impairment (MCI) is a precursor state of AD. Accurate early diagnosis of AD is …

The research of semantic segmentation networks has achieved a significant breakthrough
recently. However, most part of methods have difficulty in utilizing information generated at …

Although deep learning has achieved great success in many computer vision tasks, its
performance relies on the availability of large datasets with densely annotated samples …