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 …

To mitigate the issue of minimal intrinsic features for pure data-driven methods, in this article,
we propose a novel model-driven deep network for infrared small target detection, which …

Single-frame infrared small target detection remains a challenge not only due to the scarcity
of intrinsic target characteristics but also because of lacking a public dataset. In this paper …

Object detection that focuses on locating objects of interest and categorizing them has long
played a critical role in the development of remote sensing imagery. Following significant …

Compared with radar and visible light imaging, infrared imaging has its own unique
advantages, and in recent years, it has become a topic of intense research interest. Robust …

The detection of small infrared targets with low signal-to-noise ratios (SNRs) and contrasts in
noisy and cluttered backgrounds is challenging and therefore a domain of active research …

Excellent performance, real time and strong robustness are three vital requirements for
infrared small target detection. Unfortunately, many current state-of-the-art methods merely …

In this letter, a weighted strengthened local contrast measure (WSLCM) algorithm for
infrared (IR) small target detection is proposed, it consists of two modules, the strengthened …

The infrared (IR) small target detection algorithm with a high detection rate, low false alarm
rate, and high real-time performance has significant application value in the field of IR …

Infrared (IR) small target detection plays an important role in IR guidance systems. In this
paper, a biologically inspired method called multiscale patch-based contrast measure …