Tiny object detection is one of the challenges in the field of object detection, which can be
applied in a variety of fields. Thanks to the advances in deep learning, significant …

Ship detection plays a pivotal role in efficient marine monitoring, port management, and safe
navigation. However, the development of ship detection techniques is vastly behind other …

With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

Infrared small target detection techniques remain a challenging task due to the complex
background. To overcome this problem, by exploring context information, this research …

The past few years have witnessed the immense success of object detection, while current
excellent detectors struggle on tackling size-limited instances. Concretely, the well-known …

Object detection (OD) is a crucial computer vision task that has seen the development of
many algorithms and models over the years. While the performance of current OD models …

Benefiting from the development of convolutional neural networks (CNNs), many excellent
algorithms for object detection have been presented. Remote sensing object detection …

Remote sensing object detection (RSOD) encounters challenges in complex backgrounds
and small object detection, which are interconnected and unable to address separately. To …

FPN-based detectors have made significant progress in general object detection, eg, MS
COCO and CityPersons. However, these detectors fail in certain application scenarios, eg …

At present, the existing methods have many limitations in small target detection, such as low
accuracy, a high rate of false detection, and missed detection. This paper proposes the KPE …