Automatic Target Recognition
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Author | : Uttam K. Majumder |
Publisher | : Artech House |
Total Pages | : 290 |
Release | : 2020-07-31 |
Genre | : Technology & Engineering |
ISBN | : 1630816396 |
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Author | : Firooz Sadjadi |
Publisher | : Springer Science & Business Media |
Total Pages | : 269 |
Release | : 2007-09-04 |
Genre | : Science |
ISBN | : 0387369430 |
This book examines the roles of sensors, physics–based attributes, classification methods, and performance evaluation in automatic target recognition. It details target classification from small mine–like objects to large tactical vehicles. Also explored in the book are invariants of sensor and transmission transformations, which are crucial in the development of low latency and computationally manageable automatic target recognition systems.
Author | : David Blacknell |
Publisher | : IET |
Total Pages | : 292 |
Release | : 2013-08-23 |
Genre | : Technology & Engineering |
ISBN | : 1849196850 |
Radar Automatic Target Recognition (ATR) and NonCooperative Target Recognition (NCTR) captures material presented by leading international experts at a NATO lecture series and explores both the fundamentals of classification techniques applied to data from a variety of radar modes and selected advanced techniques at the forefront of research. The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge, although steady progress has been made over the past couple of decades. This book explores both the fundamentals of classification techniques applied to data from a variety of radar modes and selected advanced techniques at the forefront of research. Topics include: the problem as applied to the ground, air and maritime domains; impact of image quality on the overall target recognition performance; performance of different approaches to the classifier algorithm; improvement in performance to be gained when a target can be viewed from more than one perspective; ways in which natural systems perform target recognition; impact of compressive sensing; advances in change detection, including coherent change detection; and challenges and directions for future research.
Author | : Bruce J. Schachter |
Publisher | : SPIE-International Society for Optical Engineering |
Total Pages | : 254 |
Release | : 2016-03-01 |
Genre | : Algorithms |
ISBN | : 9781510600348 |
This work provides an inside view of the Automatic Target Recognition (ATR) field, from an engineer working in the field for 40 years. In many ways ATR advances follow the march of technology, including digital electronics, unmanned systems, computer vision, pattern recognition, and artificial intelligence. Algorithm descriptions and testing procedures are provided in the text. Although some of these techniques are similar to what can be found in the academic and commercial sectors, an academic or commercial perspective is inadequate to tackle the military problem. This book covers unique aspects and considerations in the design, testing and fielding of ATR systems. These aspects need to be understood by ATR engineers working in the defense industry as well as their government customers. The final chapter discusses the future of ATR. It provides a type of Turing Test for determining if an ATR is truly smart (neuromorphic or brain-like). The Appendix reveals difficult to find resources available to the "ATR engineer."
Author | : Valentina Emilia Balas |
Publisher | : Springer Nature |
Total Pages | : 500 |
Release | : 2020-08-17 |
Genre | : Technology & Engineering |
ISBN | : 3030521907 |
This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
Author | : Bruce Jay Schachter |
Publisher | : |
Total Pages | : 0 |
Release | : 2018 |
Genre | : Algorithms |
ISBN | : 9781510618565 |
"This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial Deep Learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs"--
Author | : Bhabesh Deka |
Publisher | : Springer Nature |
Total Pages | : 678 |
Release | : 2019-11-25 |
Genre | : Computers |
ISBN | : 3030348695 |
The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.
Author | : Xiaofeng Chen |
Publisher | : Springer Nature |
Total Pages | : 554 |
Release | : 2020-11-10 |
Genre | : Computers |
ISBN | : 3030624633 |
This three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Author | : Sevgi Zubeyde Gurbuz |
Publisher | : SciTech Publishing |
Total Pages | : 419 |
Release | : 2020-12-31 |
Genre | : Technology & Engineering |
ISBN | : 1785618520 |
Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking to apply these technologies ought to be aware of.
Author | : Yaakov Bar-Shalom |
Publisher | : |
Total Pages | : 474 |
Release | : 1990 |
Genre | : Radar |
ISBN | : |