The purpose of this paper is to survey and assess the state-of-the-art in automatic target
recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an …

Radar automatic target recognition (RATR) technology is fundamental but complicated
system engineering that combines sensor, target, environment, and signal processing …

This paper introduces VEDAI: Vehicle Detection in Aerial Imagery a new database of aerial
images provided as a tool to benchmark automatic target recognition algorithms in …

It is a feasible and promising way to utilize deep neural networks to learn and extract
valuable features from synthetic aperture radar (SAR) images for SAR automatic target …

We conduct an exhaustive survey of image thresholding methods, categorize them, express
their formulas under a uniform notation, and finally carry their performance comparison. The …

A new criterion for multilevel thresholding is proposed. The criterion is based on the
consideration of two factors. The first one is the discrepancy between the thresholded and …

Recent deep learning (DL) detectors adopted by radar or sonar (RS) are normally trained
with transfer learning, where the typical workflow is to pretrain a convolutional neural …

The emerging technology of multisensor data fusion has a wide range of applications, both
in Department of Defense (DoD) areas and in the civilian arena. The techniques of …

Image binarization is the process of separation of pixel values into two groups, white as
background and black as foreground. Thresholding plays a major in binarization of images …

Image segmentation is an important and fundamental task in many digital image processing
systems. Image segmentation by thresholding is the simplest technique and involves the …