Perfecting a Video Game with Game Metrics
Vol 17, No 5: October 2019

Advertisement billboard detection and geotagging system with inductive transfer learning in deep convolutional neural network

Romi Fadillah Rahmat (Universitas Sumatera Utara)
Dennis Dennis (Universitas Sumatera Utara)
Opim Salim Sitompul (Universitas Sumatera Utara)
Sarah Purnamawati (Universitas Sumatera Utara)
Rahmat Budiarto (Albaha University)

Article Info

Publish Date
01 Oct 2019


In this paper, we propose an approach to detect and geotag advertisement billboard in real-time condition. Our approach is using AlexNet’s Deep Convolutional Neural Network (DCNN) as a pre-trained neural network with 1000 categories for image classification. To improve the performance of the pre-trained neural network, we retrain the network by adding more advertisement billboard images using inductive transfer learning approach. Then, we fine-tuned the output layer into advertisement billboard related categories. Furthermore, the detected advertisement billboard images will be geotagged by inserting Exif metadata into the image file. Experimental results show that the approach achieves 92.7% training accuracy for advertisement billboard detection, while for overall testing results it will give 71,86% testing accuracy.

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Journal Info





Computer Science & IT


Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...