Title :
On learning to recognize 3-D objects from examples
Author_Institution :
Dept. of Appl. Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
fDate :
8/1/1993 12:00:00 AM
Abstract :
Previous results on nonlearnability of visual concepts relied on the assumption that such concepts are represented as sets of pixels. The author uses an approach developed by Haussler (1989) to show that under an alternative, feature-based representation, recognition is probably approximately correct (PAC) learnable from a feasible number of examples in a distribution-free manner
Keywords :
image recognition; knowledge representation; learning by example; Haussler; feature-based representation; image recognition; learning by examples; nonlearnability; visual concepts; Cognition; Computer simulation; Humans; Machine intelligence; Mathematics; Object recognition; Visual system;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
