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BL
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| Record Number
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852532
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| Main Entry
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Schachter, Bruce J., (Bruce Jay),1946-
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| Title & Author
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Automatic target recognition /\ Bruce J. Schachter.
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| Edition Statement
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Third edition.
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| Publication Statement
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Bellingham, Washington, USA :: SPIE Press,, [2018]
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, ©2018
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| Series Statement
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Tutorial texts in optical engineering ;; volume TT 118
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| Page. NO
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1 online resource (330 pages)
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| ISBN
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1510618570
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: 9781510618572
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1510618562
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1510618589
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1510618597
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9781510618565
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9781510618589
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9781510618596
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Preface -- 1. Definitions and performance measures: 1.1. What is automatic target recognition (ATR)? 1.2. Basic definitions; 1.3. Detection criteria; 1.4. Performance measures for target detection; 1.5. Classification criteria; 1.6. Experimental design; 1.7. Characterizations of ATR hardware/software -- 2. Target detection strategies: 2.1. Introduction; 2.2. Simple detection algorithms; 2.3. More-complex detectors; 2.4. Grand paradigms; 2.5. Traditional SAR and hyperspectral target detectors; 2.6. Conclusions and future direction -- 3. Target classifier strategies: 3.1. Introduction; 3.2. Main issues to consider in target classification; 3.3. Feature extraction; 3.4. Feature selection; 3.5. Examples of feature types; 3.6. Examples of classifiers; 3.7. Discussion -- 4. Unification of automatic target tracking and automatic target recognition: 4.1. Introduction; 4.2. Categories of tracking problems; 4.3. Tracking problems; 4.4. Extensions of target tracking; 4.5. Collaborative ATT and ATR (ATT<->ATR); 4.6. Unification of ATT and ATR; 4.7. Discussion -- 5. Multisensor fusion: 5.1. Introduction; 5.2. Critical fusion issues related to ATR; 5.3. Levels of fusion; 5.4. Multiclassifier fusion; 5.5. Multisensor fusion based on multiclassifier fusion; 5.6. Test and evaluation; 5.7. Beyond basic ATR fusion; 5.8. Discussion -- 6. Next-generation ATR: 6.1. Introduction; 6.2. Hardware design; 6.3. Algorithm/software design; 6.4. Potential impact.
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7. How smart is your automatic target recognizer? -- 7.1. Introduction; 7.2. Test for determining the intelligence of an ATR; 7.3. Sentient versus sapient ATR; 7.4. Discussion: where is ATR headed? -- Appendix 1: Resources -- Appendix 2: Questions to pose to the ATR customer -- Appendix 3: Acronyms and abbreviations -- Index.
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| Abstract
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"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"--
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| Subject
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Algorithms.
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Image processing.
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Optical pattern recognition.
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Radar targets.
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Algorithms.
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Image processing.
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Optical pattern recognition.
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Radar targets.
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| Dewey Classification
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623.7/348
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| LC Classification
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TK6580.S33 2018eb
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| Added Entry
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Society of Photo-optical Instrumentation Engineers,publisher.
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