1992
@article{PeL1992,
vgclass = {refpap},
vgproject = {nn,invariance},
author = {Stavros J. Perantonis and Paulo J.G. Lisboa},
title = {Translation, Rotation, and Scale Invariant Pattern
Recognition by Higher-Order Neural Networks and Moment Classifiers},
journal = {IEEE Transactions on Neural Networks},
volume = {3},
number = {2},
pages = {241--251},
month = {March},
year = {1992},
abstract = {The classification and recognition of two-dimensional
patterns independently of their position, orientation, and size by
using high-order networks are discussed. A method is introduced for
reducing and controlling the number of weights of a third-order network
used for invariant pattern recognition. The method leads to economical
networks that exhibit high recognition rates for translated, rotated,
and scaled, as well as locally distorted, patterns. The performance of
these networks at recognizing typed and handwritten numerals
independently of their position, size and orientation is compared with
and found superior to the performance of a layered feedforward network
to which image features extracted by the method of moments are
presented as input.},
}