Refereed full papers (journals, book chapters, international conferences)

1992

@article{MMI1992,
	vgclass =	{refpap},
	vgproject =	{nn,invariance},
	author =	{Jay I. Minnix and Eugene S. McVey and Rafael M.
	I\~{n}igo},
	title =	{A Multilayered Self-Organizing Artificial Neural Network
	for Invariant Pattern Recognition},
	journal =	{IEEE Transactions on Knowledge and Data Engineering},
	volume =	{4},
	number =	{2},
	pages =	{162--167},
	month =	{April},
	year =	{1992},
	abstract =	{This paper presents an artificial neural network that
	self-organizes to recognize various images presented in a training set.
	One application of the network uses multiple functionally disjoint
	stages to provide pattern recognition that is invariant to translations
	of the object in the image plane. The general form of the network uses
	three stages that perform the functionally disjoint tasks of
	preprocessing, invariance, and recognition. The Preprocessing stage is
	a single layer of processing elements that perform dynamic thresholding
	and intensity scaling. The Invariance stage is a multilayered
	connectionist implementation of a Walsh-Hadamard transform used for
	generating an invariant representation of the image. The Recognition
	stage is a multilayered self-organizing neural network that learns to
	recognize the representation of the input image generated by the
	Invariance stage. In the examples presented, the network can
	successfully self-organize to recognize objects without regard to the
	location of the object in the image field. The network also has some
	resistance to noise and distortion in the images.},
}