DocumentCode :
2029734
Title :
Rotation, size and shape recognition by a spreading neural network
Author :
Nakamura, Kiyomi ; Miyamoto, Shingo ; Yoshikawa, Tadataka
Author_Institution :
Graduate Sch. of Eng., Toyama Prefectural Univ., Japan
Volume :
3
fYear :
1999
fDate :
1999
Firstpage :
998
Abstract :
Proposes a rotation and size spreading associative neural network that recognises the size, orientation and shape of an object. This neural net uses spatial spreading by means of a double spreading layer, generalised inverse learning and population vector method for recognition of the objects. This neural net can simultaneously recognise the size of an object (irrespective of its orientation and shape), its orientation (irrespective of its size and shape) and its shape (irrespective of its size and orientation). The neural net spreads the information about the orientation and size of the object by double-spreading weights which have similar tuning characteristics to the axis-orientation neurons and size-discrimination neurons in the parietal cortex
Keywords :
neural nets; object recognition; rotation; tuning; axis-orientation neurons; double spreading layer; double-spreading weights; generalised inverse learning; orientation recognition; parietal cortex; population vector method; rotation recognition; shape recognition; size recognition; size-discrimination neurons; spatial spreading; spreading neural network; tuning characteristics; Animals; Biological neural networks; Character recognition; Electronic mail; Image sampling; Neural networks; Neurons; Pattern recognition; Pixel; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
Type :
conf
DOI :
10.1109/ICONIP.1999.844672
Filename :
844672
Link To Document :
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