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All Journal KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Christian Sanjaya
Institut Teknologi dan Bisnis Kalbis
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Journal : KALBISIANA Jurnal Sains, Bisnis dan Teknologi

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Pengembangan Model Pendeteksian Gambar Rambu Lalu Lintas dengan Metode Faster R-CNN dengan Library Tensorflow Christian Sanjaya; Henri Septanto
KALBISIANA Jurnal Sains, Bisnis dan Teknologi Vol. 8 No. 1 (2022): Kalbisiana
Publisher : UNIVERSITAS KALBIS

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Abstract

This study aims to develop a machine learning model to detect blocked traffic signals using the faster R-CNN method. Traffic signal detection is the most important part of a traffic unit. To solve this problem, the detection method relies on deep learning. The method used in this study is an image processing technique in which there is a faster R-CNN using additional stages of the search process. This research resulted in the development of a traffic light image detection model using the faster R-CNN method with a tensorflow library of traffic sign detection.
Co-Authors Henri Septanto