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Classification of Dhamma Esan Characters by Transfer Learning of a Deep Neural Network

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

We present an image classification of Dhamma Esan characters by fine-tuning the Inception V3 deep neural network trained on the ImageNet dataset. Dhamma Esan is a traditional alphabet used in the north-eastern region of Thailand, primarily written on Corypha leaves for the purpose of recording Buddhist scriptures. Preservation of these historical documents calls for the ability to classify the characters of the alphabet in order to facilitate digital indexing and searching, as well as assist anyone trying to read them. Our dataset consists of over 70,000 Dhamma Esan character images, much larger than any previous work. The result of ten-fold cross-validation showed that our model had 100% accuracy for four folds, and 99.99% for the other six folds. The previous best accuracy reported was 97.77%. We also developed a Dhamma Esan character classification web service where users can upload images of characters and get immediate classification results as well as mapping to the modern Thai alphabet.

Original languageEnglish
Title of host publicationProceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018
EditorsWudhichart Sawangphol, Jarernsri Mitrpanont
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538655382
DOIs
Publication statusPublished - 6 Sept 2018
Event15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018 - Nakhon Pathom, Thailand
Duration: 11 Jul 2018 → 13 Jul 2018

Publication series

NameProceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018

Conference

Conference15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018
Country/TerritoryThailand
CityNakhon Pathom
Period11/07/18 → 13/07/18

Keywords

  • Deep neural network
  • Dhamma Esan
  • Image classification
  • Inception-V3
  • Transfer learning

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