Abstract Recently lightweight Vision Transformers (ViTs) demonstrate superior performance
and lower latency compared with lightweight Convolutional Neural Networks (CNNs) on …

Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and
military domains. However, the high proportion of small objects in UAV images and the …

Road defect detection is a crucial task for promptly repairing road damage and ensuring
road safety. Traditional manual detection methods are inefficient and costly. To overcome …

Abstract Vision Transformer (ViT) has gained increasing attention in the computer vision
community in recent years. However the core component of ViT Self-Attention lacks explicit …

Transformer is a powerful tool for capturing long-range dependencies and has shown
impressive performance in hyperspectral image (HSI) classification. However, such power …

Change detection (CD) is a hot research topic in the remote-sensing (RS) community. With
the increasing availability of high-resolution (HR) RS images, there is a growing demand for …

Effective fusion of global and local multi-scale features is crucial for medical image
classification. Medical images have many noisy, scattered features, intra-class variations …

Timely and accurate identification of tea tree pests is critical for effective tea tree pest control.
We collected image data sets of eight common tea tree pests to accurately represent the true …

Forest fires rank among the costliest and deadliest natural disasters globally. Identifying the
smoke generated by forest fires is pivotal in facilitating the prompt suppression of developing …

Due to the depth degradation effect in residual connections many efficient Vision
Transformers models that rely on stacking layers for information exchange often fail to form …