Bleeding classification of enhanced wireless capsule endoscopy images using deep convolutional neural network
This paper investigates the performance of a Deep Convolutional Neural Network (DCNN) algorithm to identify bleeding areas of wireless capsule endoscopy (WCE) images without known prior knowledge of bleeding and normal features of the images. In this study, a pre-processing technique has been propos...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Institute of Information Science
2020
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| 主題: | |
| オンライン･アクセス: | http://umpir.ump.edu.my/id/eprint/26711/1/Bleeding%20classification%20of%20enhanced%20wireless%20capsule%20endoscopy%20images%20.pdf http://umpir.ump.edu.my/id/eprint/26711/ http://jise.iis.sinica.edu.tw/JISESearch/pages/View/PaperView.jsf?keyId=172_2294 |
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