Abstract
The ability to learn fundamental symbolic concepts, such as geometry and shape, is of interest both for complex industrial applications and for general research problems in intelligent machine vision. To these ends, the current Level I ALISA system has been enhanced to perform multi-class classification, and extended to Level II to learn and classify geometric concepts based on the texture class maps generated by Level I. Initial experiments demonstrate the successful classification and generalization of canonical and secular geometric concepts at Level II.
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© 1993 Springer-Verlag Berlin Heidelberg
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Howard, C.G., Bock, P. (1993). Multi-class classification and symbolic cognitive processing with ALISA. In: Chetverikov, D., Kropatsch, W.G. (eds) Computer Analysis of Images and Patterns. CAIP 1993. Lecture Notes in Computer Science, vol 719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57233-3_46
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DOI: https://doi.org/10.1007/3-540-57233-3_46
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