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http://repository.kalbis.ac.id/handle/123456789/209
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Septian, Ivan | - |
dc.contributor.advisor | Septanto, Henri | - |
dc.date.accessioned | 2022-06-24T22:11:50Z | - |
dc.date.available | 2022-06-24T22:11:50Z | - |
dc.date.issued | 2020-06-25 | - |
dc.identifier.uri | http://repository.kalbis.ac.id/handle/123456789/209 | - |
dc.description.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. | en_US |
dc.language.iso | other | en_US |
dc.publisher | Institut Teknologi dan Bisnis Kalbis | en_US |
dc.subject | Faster R-CNN | en_US |
dc.subject | deep learning | en_US |
dc.subject | computer vision | en_US |
dc.subject | machine learning | en_US |
dc.subject | object detection | en_US |
dc.title | Pengembangan Model Pendeteksian Gambar Alat Musik Dengan Metode Faster R-Cnn Dengan Library Keras | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | IF 2020 |
Files in This Item:
File | Description | Size | Format | |
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A_Cover_2016102301.pdf | Cover | 146.67 kB | Adobe PDF | View/Open |
B_Abstrak_2016102301.pdf | Abstrak | 138.81 kB | Adobe PDF | View/Open |
C_Daftar_isi_2016102301.pdf | Daftar isi | 154.39 kB | Adobe PDF | View/Open |
D_Bab1_2016102301.pdf | Bab 1 | 213.06 kB | Adobe PDF | View/Open |
E_Bab2_2016102301.pdf Restricted Access | Bab 2 | 361.84 kB | Adobe PDF | View/Open Request a copy |
F_Bab3_2016102301.pdf Restricted Access | Bab 3 | 1.1 MB | Adobe PDF | View/Open Request a copy |
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H_Bab5_2016102301.pdf Restricted Access | Bab 5 | 141.63 kB | Adobe PDF | View/Open Request a copy |
I_Daftar_pustaka_2016102301.pdf | Daftar pustaka | 205.27 kB | Adobe PDF | View/Open |
J_Full_text_2016102301.pdf Restricted Access | Full text | 1.97 MB | Adobe PDF | View/Open Request a copy |
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