Automatic target recognition (ATR) in synthetic aperture radar (SAR) images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a hist...

Automatic detection and recognition of targets by means of passive IR sensors suffer from limitations due to lack of sufficient contrast between the targets and their background, and among the facets of a target. In this paper the results of a suite of polarization-sensitive automatic target detection and recognition algorithms on sets of simulated and real polarimetric IR imagery ate presented...

SAR-ATR (synthetic aperture radar-automatic target recognition) is a hot topic in remote sensing. This work suggests few-shot recognition approach (FTL) based on the concept of transfer learning to accomplish accurate SAR images scenario since classic ATR method has significant data reliance. At same time, strategy introduces model distillation improve model’s performance further. composed thre...

We present an evaluation of the impact of a recently proposed synthetic aperture radar (SAR) imaging technique on feature enhancement and automatic target recognition (ATR) performance. This image formation technique is based on nonquadratic optimization, and the images it produces appear to exhibit enhanced features. We quantify such feature enhancement through a number of criteria. The findin...

This paper describes the acceleration of an infrared automatic target recognition (IR ATR) application with a co-processor board that contains multiple eld programmable gate array (FPGA) chips. Template and pixel level parallelism is exploited in an FPGA design for the bottleneck portion of the application. The implementation of this design achieved a speedup of 21 compared to running on the ho...

This paper focuses on the automatic target recognition (ATR) method based ship-radiated noise and proposes an underwater acoustic (UATR) ResNet. In proposed method, a multi-window spectral analysis (MWSA) is used to solve difficulty that traditional time–frequency (T–F) has in extracting multiple signal characteristics simultaneously. MWSA generates spectrograms with different T–F resolutions t...

In this paper we investigate techniques to train an agent to accomplish certain tasks. Artificial Neural Networks will be the technique used to the train the agent. This paper will investigate the use of Generalised Regression Neural Network (GRNN) to create and train agents capable of detecting face images. This agent would make up the ‘Detection Agent’ in an architecture comprising of several...

This paper examines metrics for measuring clutter eeectiveness on model-based automatic target recognition systems with FLIR sensors. The measure for clutter eeectiveness proposed is the diierence of two Kullback-Leibler distances between the idealized approximate probabilistic models without clutter and the real model containing clutter. We establish that occluding objects and clutter, when ma...

A tertiary goal, which we plan to explore in depth in future research, is the integration of image compression with automated target recognition (ATR). Two cases are of interest to this study. First, we have shown that one can achieve increased processing efficiency by applying specially configured ATR operations to compressed imagery [Sch97c,d]. Second, we have developed techniques for prefilt...