On Construction of Multi-class Binary Neural Network Using Fuzzy Inter-cluster Overlap for Face Recognition

  • Neha BharillEmail author
  • Om Prakash Patel
  • Aruna Tiwari
  • Megha Mantri
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)


In this paper, we propose a Novel Fuzzy-based Constructive Binary Neural Network (NF-CBNN) learning algorithm for multi-class classification. Our method draws a basic idea from Expand and Truncate Learning (ETL), which is a neural network learning algorithm. The proposed method works on the basis of unique core selection, and it guarantees to improve the classification performance by handling overlapping issues among data of various classes by using inter-cluster overlap. To demonstrate the efficacy of NF-CBNN, we tested it on the ORL face data set. The experimental results show that generalization accuracy achieved by NF-CBNN is much higher as compared to the BLTA classifier.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Neha Bharill
    • 1
    Email author
  • Om Prakash Patel
    • 1
  • Aruna Tiwari
    • 1
  • Megha Mantri
    • 2
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology IndoreIndoreIndia
  2. 2.Department of Networth the Finance Club of Indian Institute of Management BangaloreBengaluruIndia

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