| A pattern recognition based Holographic Graph Neuron for Persian alphabet recognition |
| Paper ID : 1110-MVIP2020 (R1) |
| Authors: |
|
Abdorreza Alavi gharahbagh *, Vahid Hajihashemi, Mohammad Mehdi Arab Ameri, Azam Bastanfard none,none |
| Abstract: |
| In this article a Vector Symbolic Architectures is purposed to implement a hierarchical Graph Neuron for memorizing patterns of Persian/Arabic isolated characters. The main challenge in this topic is using Vector Symbolic representation as a one-layered design for neural network while maintaining the previously reported properties and performance characteristics of hierarchical Graph Neuron. The designed architecture is robust to noise and enables a linear (with respect to the number of stored entries) time search for an arbitrary sub-pattern. The proposed method was implemented on a standard Persian database and the obtained results showed the ability of (not necessarily better) Graph neuron to recognize the Persian isolated character patterns. |
| Keywords: |
| HoloGN, Neural Network, OCR, Graph neuron, Holographic |
| Status : Paper Accepted (Oral Presentation) |
