Results 261 to 270 of about 824,134 (332)

Integrating the Reconstructed Scattering Center Feature Maps With Deep CNN Feature Maps for Automatic SAR Target Recognition

IEEE Geoscience and Remote Sensing Letters, 2021
Automatic target recognition has been one of the hottest research in synthetic aperture radar (SAR) data processing. Noticing that popular recognition methods cannot utilize multiple features of SAR complex data, a method fused scattering center feature ...
Jinsong Zhang, M. Xing, Guangcai Sun, Z. Bao   +3 more
semanticscholar   +1 more source

Hierarchical Distribution-Based Exemplar Replay for Incremental SAR Automatic Target Recognition

IEEE Transactions on Aerospace and Electronic Systems
Over the years, deep learning-based automatic target recognition (ATR) in synthetic aperture radar (SAR) imagery has made remarkable progress on the assumption that the target category library is immutable.
H. Ren, Rongsheng Zhou, Lin Zou, Hao Tang   +3 more
semanticscholar   +1 more source

Advanced Automatic Target Recognition (ATR) with Infrared (IR) Sensors

IEEE Aerospace Conference, 2021
Automatic Target Detection (ATD) and Recognition (ATR) are critical for video analysis and image understanding for many military and commercial applications deployed on satellites and UAV platforms.
Hai-Wen Chen, Neal Gross, R. Kapadia, Joseph Cheah, Mo Gharbieh   +4 more
semanticscholar   +1 more source

Sparsity inspired automatic target recognition

SPIE Proceedings, 2010
In this paper, we develop a framework for using only the needed data for automatic target recognition (ATR) algorithms using the recently developed theory of sparse representations and compressive sensing (CS). We show how sparsity can be helpful for efficient utilization of data, with the possibility of developing real-time, robust target ...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellappa   +2 more
openaire   +1 more source

Threshold-Free Open-Set Learning Network for SAR Automatic Target Recognition

IEEE Sensors Journal
Many advanced automatic target recognition (ATR) methods for synthetic aperture radar (SAR) encounter limitations, as they heavily rely on the assumption of a closed-set environment.
Yue Li, H. Ren, Xue-lian Yu, Chengfa Zhang, L. Zou, Yun Zhou   +5 more
semanticscholar   +1 more source

High performance automatic target recognition

AFRICON 2015, 2015
Designing a vision system, which was motivated by that of the human eye, has been done since the introduction of digital computing devices. Its computational complexity hinders it from the required accuracy and flexibility achievable by these systems.
Misiker Tadesse, Eneyew Adugna
openaire   +1 more source

LDGAN: A Synthetic Aperture Radar Image Generation Method for Automatic Target Recognition

IEEE Transactions on Geoscience and Remote Sensing, 2020
Under the framework of a supervised learning-based automatic target recognition (ATR) approach, recognition performance is primarily dependent on the amount of training samples. However, shortage in training samples is a consistent issue for ATR. In this
Changjie Cao, Z. Cao, Z. Cui
semanticscholar   +1 more source

Unification of Automatic Target Tracking and Automatic Target Recognition

SPIE Proceedings, 2014
The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers.
openaire   +1 more source

Automatic target recognition of ground targets

2013
An overview of the fundamentals of ground target recognition using SAR has been given. There is a tendency, when discussing ground target ATR, to consider only the most complex problems consisting of very many target classes and challenging clutter environments.
David Blacknell, Luc Vignaud
openaire   +1 more source

Polarimetrically-Persistent-Scatterer-Based Automatic Target Recognition

IEEE Transactions on Geoscience and Remote Sensing, 2011
Reliable automatic target recognition (ATR) systems based on inverse synthetic aperture radar (ISAR) images require a robust feature selection. An ATR system based on polarimetric ISAR images has been recently proposed that extracts bright scatterers and uses their polarimetric signatures to define classification features. Since bright scatterers could
GIUSTI, ELISA, MARTORELLA, MARCO, CAPRIA, AMERIGO   +2 more
openaire   +2 more sources