A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely
used for grayscale and color image segmentation. However, most of them are time …

Many state-of-the-art methods have been proposed for infrared small target detection. They
work well on the images with homogeneous backgrounds and high-contrast targets …

Robust detection of infrared small and dim targets with highly heterogeneous backgrounds
plays an indispensable role in infrared search and tracking (IRST) system, which is still a …

Infrared remote sensing imaging has a wide range of military and civilian applications. The
detection of dim small targets is one of the most valuable research topics in this field …

Infrared small target detection is an important fundamental task in the infrared system.
Therefore, many infrared small target detection methods have been proposed, in which the …

The ocean connects all continents and is an important space for human activities. Ship
detection with electro-optical images has shown great potential due to the abundant imaging …

Infrared small target detection technology is one of the key technologies in the field of
computer vision. In recent years, several methods have been proposed for detecting small …

Abstract The Fuzzy C-means (FCM) clustering algorithm is an effective method for image
segmentation. Non-local spatial information considers more redundant information of the …

Obstacle detection using semantic segmentation has become an established approach in
autonomous vehicles. However, existing segmentation methods, primarily developed for …

Despite that many state-of-the-art methods have been proposed for infrared (IR) small target
detection, target detectability (TD) and background suppressibility (BS) cannot be …