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This work explores automatic target recognition (ATR). It is divided into sections which look at topics such as: advanced systems for ATR, including airborne video surveillance; multisensor ATR; and adaptive and learning techniques for ATR.
This work explores automatic target recognition (ATR). It is divided into sections which look at topics such as: advanced systems for ATR, including airborne video surveillance; multisensor ATR; and adaptive and learning techniques for ATR.
"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"--
This 2004 book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, restoration and feature extraction, segmentation, texture and shape. They also discuss image matching, statistical pattern recognition, clustering, and syntactic pattern recognition. Important applications are described, including optical character recognition and automatic target recognition. Software and data used in the book can be found at www.cambridge.org/9780521830461. A useful reference for practitioners, the book is aimed at graduate students in electrical engineering, computer science and mathematics.
What Is Automatic Target Recognition The capacity of an algorithm or device to detect targets or other objects based on data acquired from sensors is referred to as automatic target recognition, abbreviated as ATR. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Automatic target recognition Chapter 2: Computer vision Chapter 3: Radar Chapter 4: Synthetic-aperture radar Chapter 5: Beamforming Chapter 6: Pulse-Doppler radar Chapter 7: Inverse synthetic-aperture radar Chapter 8: Radar signal characteristics Chapter 9: Time delay neural network Chapter 10: Track algorithm (II) Answering the public top questions about automatic target recognition. (III) Real world examples for the usage of automatic target recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of automatic target recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of automatic target recognition.
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.
What is Automatic Target Recognition The capacity of an algorithm or device to recognize targets or other objects based on data acquired from sensors is referred to as automatic target recognition, an abbreviation for these capabilities. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Automatic Target Recognition Chapter 2: Computer Vision Chapter 3: Radar Chapter 4: Doppler Radar Chapter 5: Synthetic-aperture Radar Chapter 6: Imaging Radar Chapter 7: Beamforming Chapter 8: Pulse-Doppler Radar Chapter 9: Passive Radar Chapter 10: Inverse Synthetic-aperture Radar (II) Answering the public top questions about automatic target recognition. (III) Real world examples for the usage of automatic target recognition in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Automatic Target Recognition.