Remote sensing (RS) images enable high-resolution information collection from complex
ground objects and are increasingly utilized in the earth observation research. Recently, RS …

Convolutional neural networks have been widely used in image semantic segmentation.
However, continuous downsampling operations in convolutional neural networks (such as …

Night-Time Scene Parsing (NTSP) is essential to many vision applications, especially for
autonomous driving. Most of the existing methods are proposed for day-time scene parsing …

Video captioning aims to generate natural language sentences that describe the given video
accurately. Existing methods obtain favorable generation by exploring richer visual …

Convolutional neural networks (CNNs) have demonstrated remarkable performance in
various computer vision tasks, such as image classification, semantic segmentation, and …

Deep learning (DL) models have recently been widely used in UAV aerial image semantic
segmentation tasks and have achieved excellent performance. However, DL models are …

Recently, transformers have been widely used in medical image segmentation to capture
long-range and global dependencies using self-attention. However, they often struggle to …

Joint access point (AP) clustering and beamforming design is an effective way to improve
system performance and reduce signaling overhead for cell-free networks. However …

In this paper, we introduce a novel Multiscale Video Transformer Network (MVTN) for
dynamic hand gesture recognition, since multiscale features can extract features with …

Semantic scene segmentation has become an important application in computer vision and
is an essential part of intelligent transportation systems for complete scene understanding of …