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Welcome to the iLab Neuromorphic Vision C++ Toolkit (iNVT)! 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++ Toolki
We describe and validate a simple context-based scene recognition algorithm using a multiscale set of early-visual features, which capture the 堵ist� of the scene into a low-dimensional signature vector. Distinct from previous approaches, the algorithm presents the advantage of being biologically plausible and of having low computational complexity, sharing its low-level features with a model for v
Bottom-Up Visual Attention Home Page We are developing a neuromorphic model that simulates which elements of a visual scene are likely to attract the attention of human observers. Given an image or video sequence, the model computes a saliency map, which topographically encodes for conspicuity (or ``saliency'') at every location in the visual input. The model predicts human performance on a number
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