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 …

Deep learning-based object detection solutions emerged from computer vision has
captivated full attention in recent years. The growing UAV market trends and interest in …

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

The prevailing applications of Unmanned Aerial Vehicles (UAVs) in transportation systems
promote the development of object detection methods to collect real-time traffic information …

Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

Object detection algorithms play an important role in maritime search and rescue missions,
where they are designed to detect people, boats and other objects in open water. However …

Directly benefiting from the deep learning methods, object detection has witnessed a great
performance boost in recent years. However, drone-view object detection remains …

Existing methods for object detection in UAV images ignored an important challenge--
imbalanced class distribution--which leads to poor performance on tail classes. We …

Detecting objects in aerial images is challenging because they are typically composed of
crowded small objects distributed non-uniformly over high-resolution (in terms of pixel size) …

Small object detection is a very challenging yet practical vision task. With deep network-
based methods, the contextual information of small objects may disappear when the network …