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

Image matting refers to extracting precise alpha matte from natural images, and it plays a
critical role in various downstream applications, such as image editing. Despite being an ill …

Cloud cover is a common and inevitable phenomenon that often hinders the usability of
optical remote sensing (RS) image data and further interferes with continuous cartography …

Deep learning methods have achieved considerable progress in remote sensing image
building extraction. Most building extraction methods are based on Convolutional Neural …

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth
observation. Clouds in optical remote sensing images seriously affect the visibility of the …

The proliferation of remote sensing satellites has resulted in a massive amount of remote
sensing images. However, due to human and material resource constraints, the vast majority …

Geographic information such as the altitude, latitude, and longitude are common but
fundamental meta-records in remote sensing image products. In this paper, it is shown that …

Field boundary data is often required to access digital agricultural services and tools that
assist with field-level assessment and monitoring. In addition, policy-makers and …

Existing deep learning-based remote sensing images semantic segmentation methods
require large-scale labeled datasets. However, the annotation of segmentation datasets is …

Clouds are a very important factor in the availability of optical remote sensing images.
Recently, deep learning (DL)-based cloud detection methods have surpassed classical …