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All Journal The Indonesian Journal of Computer Science
Novia Pramesti Aprilia
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Image Captioning untuk Gambar Rambu Lalu Lintas Indonesia Menggunakan Pretrained CNN dan Transformer Novia Pramesti Aprilia; Rochadiani, Theresia Herlina
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4012

Abstract

This research aims to address the lack of understanding of traffic signs in Indonesia through the development of an image captioning model using Inception V3 and Transformer. With this approach, a dataset of traffic sign images consisting of 9,594 images with 31 classes was collected and modified. Model evaluation was conducted using BLEU, ROUGE-L, METEOR, and CIDEr metrics. The research results show good performance with BLEU-1 score of 0.89, BLEU-2 = 0.82, BLEU-3 = 0.75, BLEU-4 = 0.68, CIDEr = 0.57, ROUGE-L = 0.25, and METEOR = 0.26. From these results, it can be indicated that this model can enhance understanding of Indonesian traffic signs. This approach can assist road users in better understanding traffic signs and has the potential to be applied in practical applications to improve traffic safety
Co-Authors Rochadiani, Theresia Herlina