A qualia exploitation of sensor technology (QUEST) motivated architecture using algorithm fusion and adaptive feedback loops\r\nfor face recognition for hyperspectral imagery (HSI) is presented. QUEST seeks to develop a general purpose computational\r\nintelligence system that captures the beneficial engineering aspects of qualia-based solutions. Qualia-based approaches are\r\nconstructed from subjective representations and have the ability to detect, distinguish, and characterize entities in the environment\r\nAdaptive feedback loops are implemented that enhance performance by reducing candidate subjects in the gallery and by injecting\r\nadditional probe images during the matching process. The architecture presented provides a framework for exploring more\r\nadvanced integration strategies beyond those presented. Algorithmic results and performance improvements are presented as\r\nspatial, spectral, and temporal effects are utilized; additionally, a Matlab-based graphical user interface (GUI) is developed to aid\r\nprocessing, track performance, and to display results.
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