Due to the rapid development of deep learning techniques, numerous frameworks including
convolutional neural networks (CNNs), deep belief networks (DBNs) and auto-encoder (AE) …

Infrared small target detection (IRSTD) refers to extracting small and dim targets from blurred
backgrounds, which has a wide range of applications such as traffic management and …

Single-frame infrared small target (SIRST) detection aims at separating small targets from
clutter backgrounds. With the advances of deep learning, CNN-based methods have yielded …

A key challenge of infrared small object segmentation (ISOS) is to balance miss detection
(MD) and false alarm (FA). This usually needs" opposite" strategies to suppress the two …

Abstract The recent Segment Anything Model (SAM) is a significant advancement in natural
image segmentation, exhibiting potent zero-shot performance suitable for various …

Space-based infrared tiny ship detection aims at separating tiny ships from the images
captured by Earth-orbiting satellites. Due to the extremely large image coverage area (eg …

Infrared small target detection (IRSTD) refers to segmenting the small targets from infrared
images, which is of great significance in practical applications. However, due to the small …

Single-frame infrared small target detection (SIRSTD) is in urgent demand for many practical
tasks, such as fire rescue and urban management systems, benefiting from the excellent …

Single-frame infrared small target detection is still a challenging task due to the complex
background and unobvious structural characteristics of small targets. Recently …

The development of fully autonomous seafaring vessels has enormous implications to the
world's global supply chain and militaries. To obey international marine traffic regulations …