In recent years, the realm of deep learning has witnessed significant advancements,
particularly in object detection algorithms. However, the unique challenges posed by remote …

Existing remote sensing image salient object detection (RSI-SOD) methods widely perform
object-level semantic understanding with pixel-level supervision, but ignore the image-level …

Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …

Background The approaches based on vision transformers (ViTs) are advancing the field of
medical artificial intelligence (AI) and cancer diagnosis. Recently, many researchers have …

Deep learning-based object detectors in remote sensing (RS) scenarios typically follow the
paradigm of pretraining and fine-tuning to alleviate the limitation of insufficient downstream …

Anomaly detection is an area of video analysis and plays an increasing role in ensuring
safety, preventing risks, and guaranteeing quick response in intelligent surveillance …

With a focus on abnormal events contained within untrimmed videos, there is increasing
interest among researchers in video anomaly detection. Among different video anomaly …

Unsupervised domain adaptation (UDA) is critical for remote sensing object detection in real
applications, aiming to address the significant performance degradation issue caused by the …

Satellite remote sensing technology significantly contributes to intelligent transportation by
optimizing traffic planning via global perspectives and rich data, enhancing traffic efficiency …

In the field of Earth observation and computer vision, oriented object detection for
remotesensing images is a crucial task that aims to locate objects more accurately in …