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

1994

@article{DTK1994,
	vgclass =	{refpap},
	vgproject =	{nn,invariance},
	author =	{Anastasios Delopoulos and Andreas Tirakis and Stefanos
	Kollias},
	title =	{Invariant Image Classification Using
	Triple-Correlation-Based Neural Networks},
	journal =	{IEEE Transactions on Neural Networks},
	volume =	{5},
	number =	{3},
	pages =	{392--408},
	month =	{May},
	year =	{1994},
	abstract =	{Triple-correlation-based neural networks are introduced
	and used in this paper for invariant classification of two-dimensional
	gray scale images. Third-order correlations of an image are
	appropriately clustered, in spatial or spectral domain, to generate an
	equivalent image representation that is invariant with respect to
	translation, rotation, and dilation. An efficient implementation scheme
	is also proposed, which is robust to distortions, insensitive to
	additive noise, and classifies the original image using adequate neural
	network architectures applied directly to 2-D image representations.
	Third-order neural networks are shown to be a specific category of
	triple-correlation-based networks, applied either to binary or
	gray-scale images. A simulation study is given, which illustrates the
	theoretical developments, using synthetic and real image data.},
}