Small object detection is a challenging problem in computer vision. It has been widely
applied in defense military, transportation, industry, etc. To facilitate in-depth understanding …

Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate
negatively impacted communal health and global economy, with the brim-full horizon yet to …

Although great progress has been made in generic object detection by advanced deep
learning techniques, detecting small objects from images is still a difficult and challenging …

Small object detection remains an unsolved challenge because it is hard to extract the
information of small objects with only a few pixels. While scale-level corresponding detection …

In real life, object detection is widely applied and plays a significant part in the field of
computer vision. However, when detecting small objects, the advanced You Only Look Once …

With the increase of training data and the improvement of machine performance, the object
detection method based on convolutional neural network (CNN) has become the …

In spite of recent success of proposal-based CNN models for object detection, it is still
difficult to detect small objects due to the limited and distorted information that small region …

Object detectors have improved in recent years, obtaining better results and faster inference
time. However, small object detection is still a problem that has not yet a definitive solution …

Recent state-of-the-art detectors generally exploit the Feature Pyramid Networks (FPN) due
to its advantage of detecting objects at different scales. Despite significant advances in …