Using Artificial Neural Networks to Identify Headings in Newspaper Documents

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

Several features for Neural Network based document region identification are tested. Specifically, this paper examines features for headline and subheadline region identification. The Neural Network based region identification algorithm is a key component of a document recognition system that segments a document into regions, classifies them into text, graphic, photo, and other region types, and then uses this classification to guide the processing and analysis of the image. The input data are unusually challenging: low quality images of newspaper documents obtained from microfilmed archives. Experiments on several newspaper documents show that the features used are capable of robust and accurate headline identification.

Original languageEnglish
Pages2283-2287
Number of pages5
StatePublished - 2003
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: 20 Jul 200324 Jul 2003

Conference

ConferenceInternational Joint Conference on Neural Networks 2003
Country/TerritoryUnited States
CityPortland, OR
Period20/07/0324/07/03

Fingerprint

Dive into the research topics of 'Using Artificial Neural Networks to Identify Headings in Newspaper Documents'. Together they form a unique fingerprint.

Cite this