• Title/Summary/Keyword: Multi-Layer Neural Networks (MLNN)

Search Result 2, Processing Time 0.018 seconds

Recurrent Based Modular Neural Network

  • Yon, Jung-Heum;Park, Woo-Kyung;Kim, Yong-Min;Jeon, Hong-Tae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2003.09a
    • /
    • pp.694-697
    • /
    • 2003
  • In this paper, we propose modular network to solve difficult and complex problems that are seldom solved with Multi-Layer Neural Network(MLNN). The structure of Modular Neural Network(MNN) in researched by Jacobs and jordan is selected in this paper. Modular network consists of several Expert Networks(EN) and a Gating Network(CN) which is composed of single-layer neural network(SLNN) or multi-layer neural network. We propose modular network structure using Recurrent Neural Network(RNN), since the state of the whole network at a particular time depends on aggregate of previous states as well as on the current input. Finally, we show excellence of the proposed network compared with modular network.

  • PDF

Real Time Face Detection and Recognition using Rectangular Feature Based Classifier and PCA-based MLNN (사각형 특징 기반 분류기와 PCA기반 MLNN을 이용한 실시간 얼굴검출 및 인식)

  • Kim, Jong-Min;Lee, Kee-Jun
    • Journal of Digital Contents Society
    • /
    • v.11 no.4
    • /
    • pp.417-424
    • /
    • 2010
  • In this paper the real-time face region was detected by suggesting the rectangular feature-based classifier and the robust detection algorithm that satisfied the efficiency of computation and detection performance was suggested. By using the detected face region as a recognition input image, in this paper the face recognition method combined with PCA and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input face image, this method computes the eigenface through PCA and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the face recognition is performed by inputting the multi-layer neural network.