An Implementation of Generalized Second-Order Neural Networks for Pattern Recognition

패턴인식을 위한 일반화된 이차신경망 구현

  • 이봉규 (제주대학교 전산통계학과) ;
  • 양요한 (제주대학교 전산통계학과)
  • Published : 2002.10.01

Abstract

For most of pattern recognition applications, it is required to correctly recognize patterns even if they have translation variations. In this paper, to achieve the goal of translation invariant pattern recognition, we propose a new generalized translation invariant second-order neural network using a constraint on the weights. The weight constraint is implemented using generalized translation invariant features which are accumulated sums of pixel combinations. Simulation results will be given to demonstrate that the proposed second-order neural network has the generalized translation invariant property.

Keywords

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