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19 May 2020 Image fusion for context-aided automatic target recognition
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Abstract
Automatic Target Recognition (ATR) has seen many recent advances from image fusion, machine learning, and data collections to support multimodal, multi-perspective, and multi-focal day-night robust surveillance. This paper highlights ideas, strategies, and concepts as well as provides an example for electro-optical and infrared image fusion cooperative intelligent ATR analysis. The ATR results support simultaneous tracking and identification for physicsbased and human-derived information fusion (PHIF). The importance of context serves as a guide for ATR systems and determines the data requirements for robust training in deep learning approaches.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erik Blasch, Zheng Liu, and Yufeng Zheng "Image fusion for context-aided automatic target recognition", Proc. SPIE 11394, Automatic Target Recognition XXX, 113940U (19 May 2020); https://doi.org/10.1117/12.2564876
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