Since only the spatial feature information of ship target is utilized, the current deep learning-
based synthetic aperture radar (SAR) ship detection approaches cannot achieve a …

Deep learning is currently the mainstream method of object detection. Faster region-based
convolutional neural network (Faster R-CNN) has a pivotal position in deep learning. It has …

Synthetic aperture radar (SAR) ship detection is sensitive to the interference of inshore
background, disturbance of strong wind and waves. The similar textures of the neighbor …

The objective of generalized sampling expansion (GSE) is the reconstruction of an
unknown, continuously defined function f (t) from samples of the responses from M linear …

In a wide range of image processing and computer vision problems, line segment detection
is one of the most critical challenges. For more than three decades researchers have …

Real-time radial velocity estimation is a key challenge for moving target imaging and
location in current single-antenna synthetic aperture radar (SAR)-ground moving target …

In view of the shortcomings of current image detection methods for icing thickness on power
transmission lines, an image measuring method for icing thickness based on remote online …

It is an important work to classify the modulation type of the intercepted radar signal for an
electronic intelligence (ELINT) receiver in a non-cooperative environment. The authors use …

Intelligent detection of locomotive signal lights and pedestrians on railway tracks is of great
significance to the safe operation of locomotives, especially under bad illumination …

Object detection has experienced a surge in interest due to its relevance in video analysis
and image interpretation. Traditional object detection approaches relied on handcrafted …