Please use this identifier to cite or link to this item: http://repository.kalbis.ac.id/handle/123456789/209
Title: Pengembangan Model Pendeteksian Gambar Alat Musik Dengan Metode Faster R-Cnn Dengan Library Keras
Authors: Septian, Ivan
Septanto, Henri
Keywords: Faster R-CNN
deep learning
computer vision
machine learning
object detection
Issue Date: 25-Jun-2020
Publisher: Institut Teknologi dan Bisnis Kalbis
Abstract: This research discusses developing a musical instrument image detection application with a frcnn library method. The purpose of this study is to detect types of musical instruments using the fastest R-CNN as a method of detecting objects. The problem with using RCNN is the length of time of computing. It takes about a minute to process the image data, so the training process will take a very long time. Therefore, researchers use the fastest r-cnn method to get the output quickly.
URI: http://repository.kalbis.ac.id/handle/123456789/209
Appears in Collections:IF 2020

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