This paper provides an overview of existing literature on vessel/ship detection and
classification from optical satellite imagery. Although SAR (Synthetic Aperture Radar) is still …

Considering the important applications in the military and the civilian domain, ship detection
and classification based on optical remote sensing images raise considerable attention in …

Ship recognition in high-resolution optical satellite images is an important task. However, it
is difficult to recognize ships under complex backgrounds, which is the main bottleneck for …

In this paper, we introduce a new large-scale dataset of ships, called SeaShips, which is
designed for training and evaluating ship object detection algorithms. The dataset currently …

Semantic segmentation is an extremely challenging task in high-resolution remote sensing
(HRRS) images as objects have complex spatial layouts and enormous variations in …

Due to the rapid development of deep learning techniques, numerous frameworks including
convolutional neural networks (CNNs), deep belief networks (DBNs) and auto-encoder (AE) …

Ship detection is an important and challenging task in remote sensing applications. Most
methods utilize specially designed hand-crafted features to detect ships, and they usually …

Automatic ship detection on spaceborne optical images is a challenging task, which has
attracted wide attention due to its extensive potential applications in maritime security and …

Ship detection is an important but challenging task in the field of computer vision, partially
due to the minuscule ship objects in optical remote sensing images and the interference of …

The automatic ship detection method for thermal infrared remote sensing images (TIRSIs) is
of great significance due to its broad applicability in maritime security, port management …