Title :
A model of human knowledge and recognition system based on similarity transformation
Author_Institution :
Sch. of Comput., Canberra Univ., ACT, Australia
Abstract :
We propose a model of human knowledge acquisition and recognition process based on a theoretical foundation: similarity transformation. The model is an artificial neural network for pattern recognition (PRANN). Different from conventional ANNs, PRANN has the ability to retrieve individual stored objects, and the recognition process can stop at any sensitivity level at which an abstract image of any abject can be obtained. Based on abstract images, full details of stored images can be recovered approximately
Keywords :
knowledge acquisition; neural nets; pattern recognition; PRANN; abstract images; human knowledge acquisition; human knowledge model; individual stored objects; pattern recognition artificial neural network; recognition process; recognition system; sensitivity level; similarity transformation; stored images; theoretical foundation; Artificial neural networks; Australia; Fuzzy sets; Humans; Image recognition; Image retrieval; Information retrieval; Knowledge acquisition; Mathematical model; Pattern recognition;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820212
