High-quality land-use/land-cover mapping with optical remote sensing images yet presents
significant work. Even though fully convolutional semantic segmentation models have …

Infrared small-target detection (ISTD) is an important computer vision task. ISTD aims at
separating small targets from complex background clutter. The infrared radiation decays with …

Smart UAVs have been developed under the consumer Internet of Drone Things (CIoDTs)
framework to improve the quality of service (QoS) for several commercial and consumer …

Accurate extraction of urban features such as buildings and roads lays the foundation for the
current trends of digital twins of urban systems to support planning, monitoring, navigation …

Bearings are an essential component of modern industry and cross-domain diagnosis of
bearings holds significant importance. However, in practical applications, issues such as …

The classification of seabed sediments is an essential aspect of marine spatial planning and
management. Multibeam echo sounders (MBESs) have been widely used for efficient and …

In recent years, convolutional neural networks (CNNs) have gained widespread adoption in
remote sensing image processing. Deploying CNN-based algorithms on satellite edge …

Deep neural networks (DNNs) have attained remarkable success in aerial detection tasks,
yet they remain susceptible to adversarial samples, posing a significant challenge for their …

The emergence of deep learning-based classification methods has led to considerable
advancements and remarkable performance in image recognition. This study introduces the …

Semantic segmentation of aerial images plays a pivotal role in extracting detailed
information about land cover, infrastructure, and natural features. Traditional single-channel …