Search results for key=SqC1997 : 1 match found.

1997

• @techreport{SqC1997,
  	vgclass =	{report},
  	vgproject =	{nn,invariance},
  	author =	{David McG. Squire and Terry M. Caelli},
  	title =	{Invariance Signatures: Characterizing contours by their
  	departures from invariance},
  	number =	{97.04},
  	institution =	{Computer Vision Group,  Computing Centre, University
  	of Geneva},
  	address =	{rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve,
  	Switzerland},
  	month =	{April},
  	year =	{1997},
  	url =	{/publications/postscript/1997/VGTR97.04_SquireCaelli.pdf},
  	url1 =	{/publications/postscript/1997/VGTR97.04_SquireCaelli.ps.gz},
  	abstract =	{In this paper, a new invariant feature of two-dimensional
  	contours is reported: the Invariance Signature. The Invariance
  	Signature is a measure of the degree to which a contour is invariant
  	under a variety of transformations, derived from the theory of Lie
  	transformation groups. Since it is derived from local properties of the
  	contour, it is well-suited to a neural network implementation. It is
  	shown that a Model-Based Neural Network (MBNN) can be constructed which
  	computes the Invariance Signature of a contour, and classifies patterns
  	on this basis. Experiments demonstrate that Invariance Signature
  	networks can be employed successfully for shift-, rotation- and
  	scale-invariant optical character recognition.},
  }