The presence of clouds prevents optical satellite imaging systems from obtaining useful
Earth observation information and negatively affects the processing and application of …

Cloud detection is a crucial preprocessing step for optical satellite remote sensing (RS)
images. This article focuses on the cloud detection for RS imagery with cloud-snow …

Using state-of-the-art artificial intelligence (AI) frameworks onboard spacecraft is challenging
because common spacecraft processors cannot provide comparable performance to …

In space science and satellite imagery, better resolution of the data information obtained
makes images clearer and interpretation more accurate. However, the huge data volume …

Semantic segmentation methods have made impressive progress with deep learning.
However, while achieving higher and higher accuracy, state-of-the-art neural networks …

The synthetic aperture radar (SAR) imagery has been widely applied for flooding mapping
based on change detection approaches. However, errors in the mapping result are expected …

The detection of clouds in remote sensing (RS) images is an important task, and
convolutional neural networks (CNNs) have been used to perform it. However, supervised …

Accurate cloud and shadow detection is a crucial prerequisite for optical remote sensing
image analysis and application. Multi-temporal-based cloud and shadow detection methods …

Cloud detection methods based on deep learning depend on large and reliable training
datasets to achieve high detection accuracy. There will be a significant impact on their …

In livestock industry, the female and male pigeons have different follow-up functions. The
discrimination of female and male pigeons is an intensive concern for breeding tasks. In …