Classification for multiformat object of cultural heritage using deep learning

Ridwan Andi Kambau, Zainal Arifin Hasibuan, M. Octaviano Pratama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The growth of information in the last two decades is dominated by multimedia data such as text, image, audio, and video. Multimedia data with low-level features should be represented in a high-level concept that is easily understood by a human. Classification of the multi-format object is a technique that is used to represent a multi-source object like text, image, audio, and video at once. The object t features are extracted then categorized in several specified classes or concepts. This paper adopts Deep Learning Techniques: (1) Convolutional Neural Networks (CNN) techniques for classifying an image, audio, and video, (2) Recurrent Neural Networks (RNN) technique for classifying text. The experiment uses small data of Indonesian cultural heritage domain. As supervised learning form, the output model is grouped into five classes based on Indonesian ethnic groups (Toraja, Bali, Batak, Dayak, Betawis. The result, this classification model can be implemented in the Multimedia Information Retrieval System and Recommender System for Indonesia Cultural Heritage.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Informatics and Computing, ICIC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538669204
DOIs
Publication statusPublished - 1 Oct 2018
Event3rd International Conference on Informatics and Computing, ICIC 2018 - Palembang, Indonesia
Duration: 17 Oct 201818 Oct 2018

Publication series

NameProceedings of the 3rd International Conference on Informatics and Computing, ICIC 2018

Conference

Conference3rd International Conference on Informatics and Computing, ICIC 2018
Country/TerritoryIndonesia
CityPalembang
Period17/10/1818/10/18

Keywords

  • Classification multi-format Object
  • Convolutional neural network
  • Cultural Heritage
  • Deep learning
  • Recurrent neural network

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