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SHOSLIF: a framework for object recognition from images

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1 Author(s)
Weng, J. ; Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA

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

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994