A novel learning method by structural reduction of DAGs for on-line OCR applications

I. Jong Lin, S. Y. Kung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper introduces a learning algorithm for a neural structure, directed acyclic graphs (DAGs) that is structurally based, i.e. reduction and manipulation of internal structure are directly linked to learning. This paper extends the concepts of I-Jong Lin and Kung (see IEEE Transactions in Signal Processing Special Issue Neural Networks, 1996) for template matching to a neural structure with capabilities for generalization. DAG-learning is derived from concepts in finite state transducers, hidden Markov models, and dynamic time warping to form an algorithmic framework within which many adaptive signal techniques such as vector quantization, K-means, approximation networks, etc., may be extended to temporal recognition. The paper provides a concept of path-based learning to allow comparison among hidden Markov models (HMMs), finite state transducers (FSTs) and DAG-learning. The paper also outlines the DAG-learning process and provides results from the DAG-learning algorithm over a test set of isolated cursive handwriting characters.

Original languageEnglish (US)
Title of host publicationProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
Pages1069-1072
Number of pages4
DOIs
StatePublished - Dec 1 1998
Event1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 - Seattle, WA, United States
Duration: May 12 1998May 15 1998

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Other

Other1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
CountryUnited States
CitySeattle, WA
Period5/12/985/15/98

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A novel learning method by structural reduction of DAGs for on-line OCR applications'. Together they form a unique fingerprint.

  • Cite this

    Lin, I. J., & Kung, S. Y. (1998). A novel learning method by structural reduction of DAGs for on-line OCR applications. In Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 (pp. 1069-1072). [675453] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2). https://doi.org/10.1109/ICASSP.1998.675453