【2018.03】自动目标识别（第三版）Automatic Target Recognition, Third Edition，共330页。
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ATR定义与性能衡量
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目标检测策略
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目标分类器策略
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自动目标跟踪与自动目标识别的统一
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多传感器融合
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下一代ATR
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自动目标识别器的智能化程度究竟如何呢？
附录A ATR资源
附录B 向ATR需求客户提出的问题
附录C 缩略语
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《自动目标识别》第三版为ATR设计的突破提供了路线图，增加了智能、性能和自主性。
This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs―with increased intelligence, performance, and autonomy.
对军事问题和类似的商业化深度学习问题进行了明确的区分。
Clear distinctions are made between military problems and comparable commercial deep-learning problems.
在国防工业工作的ATR工程师以及他们的政府客户需要充分理解这些考虑因素。
These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers.
本书为不断学习并适应其环境的下一代ATR提供了参考设计。
A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment.
单个平台上不同形式的数据融合支持了ATR新的功能和改进的性能。
The convergence of diverse forms of data on a single platform supports new capabilities and improved performance.
第三版拓宽了ATR到多传感器融合的概念。
This third edition broadens the notion of ATR to multisensor fusion.
彻底地持续学习ATR体系架构、更好的数据源集成、封装良好的传感器和低功耗的teraflop芯片将使军事设计产生变革性的进展。
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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