The iLab Neuromorphic Vision C++ Toolkit (iNVT, pronounced “invent”) is a comprehensive set of C++ classes for the development of neuromorphic models of vision. Neuromorphic models are computational neuroscience algorithms whose architecture and function is closely inspired from biological brains. The iLab Neuromorphic Vision C++ Toolkit comprises not only base classes for images, neurons, and brain areas, but also fully-developed models such as our model of bottom-up visual attention and of Bayesian surprise
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References in zbMATH (referenced in 1 article )
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- Shic, Frederick; Scassellati, Brian: A behavioral analysis of computational models of visual attention (2007)
Further publications can be found at: http://ilab.usc.edu/toolkit/publications.shtml