"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 teraflopchips will enable transformative military designs"-- Read more...
Abstract:
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. Read more...
Author(s): Schachter, Bruce Jay
Series: Tutorial texts in optical engineering TT 118
Edition: Third edition
Publisher: SPIE Press
Year: 2018
Language: English
Pages: 307
Tags: Algorithms.;Image processing.;Optical pattern recognition.;Radar targets.;Algorithmes.;Cibles radars.;Reconnaissance optique des formes (Informatique);Traitement d'images.
Content: Definitions and performance measures --
Target detection strategies --
Target classifier strategies --
Unification of automatic target tracking and automatic target recognition --
Multisensor fusion --
Next-generation ATR --
How smart is your automatic target recognizer?
