Garbled Text String Recognition with a Spatio-Temporal Pattern Recognition Neural Network (Verminkte Tekst String Herkenning met een Spatio-Temporeel Patroon Herkennings Neuraal Netwerk)

Abstract

The purpose of this project is to show that neural networks can be used to recognize garbled words and/or parts of sentences in a real-world application. TNO-FEL has studied and built an application that recognizes the names of ships. These names may be garbled by transmission or typing errors, and synonyms or corruptions may be used. The SPR network emphasizes the character- sequence relationships within words. SPR is proof against missing, extra or interchanged (pairs of) characters. A learning strategy was developed and implemented. Several measurements were performed. Keywords: Netherlands.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1990
Accession Number
ADA226727

Entities

People

  • P. P. Meiler

Organizations

  • Netherlands Organisation for Applied Scientific Research

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Software
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Content Addressable Memory
  • Dimensionality Reduction
  • Electronics Laboratories
  • Information Systems
  • Measurement
  • Neural Networks
  • Pattern Recognition
  • Self Organizing Systems
  • Signal Processing
  • Supervised Machine Learning

Readers

  • Computer Programming and Software Development.
  • Computer Vision.
  • Marine Propulsion Engineering and Naval Architecture

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks