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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Zohanto Widyantoko
Center of Handicraft and Batik Yogyakarta
Computer Science & IT Engineering

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Expert role in image classification using CNN for hard to identify object: distinguishing batik and its imitation Zohanto Widyantoko; Titik Purwati Widowati; Isnaini Isnaini; Paras Trapsiladi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i1.pp93-100

Abstract

In this research we try to solve the recognition problem in differentiating between batik and its imitation. Batik is an Indonesian heritage of process in making traditional textile product that is now endangered by the existence of imitation products. We try to compare two popular CNN model to classify batik products into five classes. The classes are tulis, cap, print warna, print malam, cabut warna. Tulis and cap are genuine batik, and the other three are an imitation. We realize that this problem is go beyond the recognition of fine grained image problem, it is a hard to identify image problem because even the batik experts is having a hard time identifying batik and its imitation if only based on its picture. The two CNN models, inceptionV3 and mobilenetV2 were trained on three types of image. One type is a freely taken image, the other two were taken based on the experts suggestion. The accuracy score shows that the model trained with the suggestion based picture perform better than the one trained with the random picture.
Co-Authors Isnaini Isnaini Paras Trapsiladi Titik Purwati Widowati