SHOSLIF: a framework for object recognition from images

A new framework called self-organizing hierarchical optimal subspace learning and inference framework (SHOSLIF) is introduced for recognizing and segmenting real-world objects from images. It addresses critical problems in real-world recognition including visual attention, feature representation efficiency, shape variation in unsegmented data (including size, position and orientation), decision optimality, and geometric inference.<
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