Fast and robust small target detection is one of the key technologies in the infrared (IR)
search and tracking systems. With the development of deep learning, there are many data …

Existing infrared (IR) small target detection algorithms often lack adaptability in complex
scenes and heavily rely on parameter configurations. To address this limitation, we propose …

Single-frame infrared small target (SIRST) detection has been a challenging task due to a
lack of inherent characteristics, imprecise bounding box regression, a scarcity of real-world …

Efficiently and accurately separating infrared (IR) small targets from complex backgrounds
presents a significant challenge. Numerous studies in the literature have proposed various …

The infrared small and dim (S&D) target detection is one of the key techniques in the infrared
search and tracking system. Since the local regions similar to infrared S&D targets spread …

Extracting small targets from complex backgrounds is the eventual goal of single-frame
infrared small target detection, which has many potential applications in defense security …

Many existing low-rank methods have achieved good detection performance in uniform
scenes, but they suffer from a high false alarm rate in complex noisy scenes. Therefore, it is …

Existing low-rank methods usually introduce manifold learning to achieve good detection
performance in complex scenes. However, these methods suffer from high computational …

Infrared dim small target (IDST) detection holds significant importance in early target
warning and ground monitoring. However, IDST detection remains a long-standing …

With the continuous progress in optical sensor technologies, the emergence of imagery
detection systems operating in the infrared (IR) band has become a reality. In response, we …