Implementation of Handwritten Character Recognition using ANN and HCNN

Authors

  • Vijaylaxmi  Department of Digital Communication and Networking, Godutai Engineering College for Women, Kalaburagi, Karnataka, India 2Department of Electronics and Communication Engineering, Godutai Engineering College for Women, Kalaburagi, Karnataka, India
  • Vinita Patil  

Keywords:

Cooperative, Neural, HCCNN.

Abstract

The paper concentrates on a concealed control neural system (HCNN) based A"/HMM half breed approach which handles all the while both the worldwide pattem class variety and the neighborhood flag primitive variety. Gee is utilized, at the pattern class level to arrange diverse primitives in different requests. One HCNN is connected to demonstrate flag primitives in each HMM state as the outflow likelihood estimator. The control flag of HCNN adapts to the primitive variety retention assignment. The proposed technique was connected to the on-line cursive penmanship acknowledgment issue and contrasted and our past comparative frameworks on the UNIPEN penmanship database.

References

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Published

2017-10-31

Issue

Section

Research Articles

How to Cite

[1]
Vijaylaxmi, Vinita Patil, " Implementation of Handwritten Character Recognition using ANN and HCNN, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.914-917, September-October-2017.