Biomimicry is a new discipline that studies nature's best ideas and then imitates these designs and processes to solve difficult problems. Humans are better at detecting and recognizing targets in literal imagery than any known algorithm. Recent advances in modeling visual processes result from functional magnetic resonance imaging experiments with humans and the use of more invasive techniques with monkeys. A block diagram of the basic modules of the human visual cortex has been pieced together, relying on the neuroscience literature. The visual cortex is just beginning to be understood. The neuroscience literature is vast and growing, leading to different explanations of function and different partitions of the cortex into modules. There are also some differences between the visual cortices of humans and monkeys. The findings that we draw from the neuroscience literature are speculative. We pick from among these findings and give them engineering, rather than a biological interpretation. The objective is to develop a biologically inspired model of early visual processing suitable for real-time implementation in electronic hardware. The objective is not to faithfully model the complete biological system, because electronic hardware cannot now mimic a cortex-size neural array with trillions of synaptic connections (let alone at the genetic level, molecular level, hierarchical circuit level, etc.), military sensors do not function like a pair of retinae or eyeballs, imaging sensors are not mounted onto humanoid robots with feedback from, and motor control of, eyeball, neck, and body movements, military objects of interest (long-range targets) are more limited and of lower resolution than items of general human interest such as food, tools, faces, places and anything else affecting survival, and a lifetime of visual learning does not match the military hardware development cycle.


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    Title :

    Closed-loop neuromorphic target cuer


    Contributors:


    Publication date :

    2013-08-01


    Size :

    1341526 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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