Semantic segmentation of high-resolution remote sensing images is highly challenging due
to the presence of a complicated background, irregular target shapes, and similarities in the …

In feature-based remote sensing image registration, the scale-invariant feature transform
(SIFT) algorithm has been one of the most popular solutions. However, it is still a challenge …

Detecting objects in aerial images is a challenging task due to multiple orientations and
relatively small size of the objects. Although many traditional detection models have …

Animals have certain cognitive competence about the environment so they can correct their
navigation errors. Inspired by the excellent navigational behavior of animals, this paper …

Nowadays, several remote sensing image capturing technologies are used ranging from
unmanned aerial vehicles to satellites. Powerful learning-based discriminative features play …

The roof plane segmentation is one of the key issues for constructing accurate three-
dimensional building models from airborne light detection and ranging (LiDAR) data …

Automatic image registration has been wildly used in remote sensing applications. However,
the feature-based registration method is sometimes inaccurate and unstable for images with …

Based on characteristics or similarity metrics, image registration aligns various images
acquired at different time frames or from different points of view. This is a common issue in …

Social media makes it easy for individuals to publish and consume news, but it also
facilitates the spread of rumors. This paper proposes a novel deep recurrent neural model …

Image registration is widely used in many fields, but the adaptability of the existing methods
is limited. This work proposes a novel image registration method with high precision for …