Abstract

Through digitization, maintaining and promoting cultural heritage is being strengthened. Concerning this background, this study presents a new Indonesia cultural events dataset and automatic image classification for cultural events. The dataset was developed using the Flickr image platform, and the five cultural events image was collected including the Baliem Festival, Jember Fashion Festival, Nyepi Festival, Pacu Jawi, and Pasola Festival. Further, Convolutional Neural Networks (CNN) was developed for the classification method. A comparison of CNN models (VGG16 and VGG19) using several optimization configurations was performed to get the best model. The results showed that the VGG16 with image augmentation and dropout regularization technique performed best with 94.66% accuracy. This study hoped to support the heritage's digital documentation process and preserve Indonesia's cultural heritage.

Highlights

  • Cultural events are created based on social systems or cultural wisdom passed from one generation to another [1], [2]

  • EXPERIMENTAL RESULTS This section explains the analysis of the obtained algorithm's performance on the cultural events dataset

  • This study presents a new Indonesia cultural events dataset and automatic image recognition for classification cultural events

Read more

Summary

Introduction

Cultural events are created based on social systems or cultural wisdom passed from one generation to another [1], [2]. They have historical roots, customs, values, and beliefs influenced by many aspects such as region, social, and culture [3]. Understanding cultural values benefits maintaining cultural heritage [4]. As stated by The United Nations Educational, Scientific, and Cultural Organization (UNESCO) mission, every country is encouraged to approve the World Heritage Convention and ensure the identification, protection, and preservation of its cultural heritage [5]. It is essential to sustain the cultural heritage in the face of rapid globalization in line with UNESCO's mission

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call