Please use this identifier to cite or link to this item: http://repository.kalbis.ac.id/handle/123456789/209
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dc.contributor.authorSeptian, Ivan-
dc.contributor.advisorSeptanto, Henri-
dc.date.accessioned2022-06-24T22:11:50Z-
dc.date.available2022-06-24T22:11:50Z-
dc.date.issued2020-06-25-
dc.identifier.urihttp://repository.kalbis.ac.id/handle/123456789/209-
dc.description.abstractThis 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.en_US
dc.language.isootheren_US
dc.publisherInstitut Teknologi dan Bisnis Kalbisen_US
dc.subjectFaster R-CNNen_US
dc.subjectdeep learningen_US
dc.subjectcomputer visionen_US
dc.subjectmachine learningen_US
dc.subjectobject detectionen_US
dc.titlePengembangan Model Pendeteksian Gambar Alat Musik Dengan Metode Faster R-Cnn Dengan Library Kerasen_US
dc.typeThesisen_US
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