Search Results - "Choirunnisa, Shabrina"

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  1. 1

    Interactive Image Segmentation using Neighborhood Spatial Information and Statistical Grey Level on Dental Panoramic Radiograph by Choirunnisa, Shabrina, Firmanto, Ari, Zaenal, Agus

    “… In dental panoramic radiographs, grey-level intensity information has been widely used for object segmentation in digital image. However, low contrast in the…”
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    Journal Article
  2. 2

    Hybrid Method of Undersampling and Oversampling for Handling Imbalanced Data by Choirunnisa, Shabrina, Lianto, Joko

    “…Imbalance of data occurs in various kinds of data including natural imbalanced data. If the computation process of the imbalanced data is carried out (for…”
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    Conference Proceeding
  3. 3

    Software Defect Prediction using Oversampling Algorithm: A-SUWO by Choirunnisa, Shabrina, Meidyani, Biandina, Rochimah, Siti

    “…To predict software defects required prediction models using defect data and software metrics called Software Defect Prediction (SDP). Some learning algorithms…”
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    Conference Proceeding
  4. 4

    Optimization of forecasted port container terminal performance using goal programming by Choirunnisa, Shabrina, Sarno, Riyanarto, Fauzan, Abd. Charis

    “…A company that has several goals (multi-purpose) to achieve, such as maximizing total sales, maximize production and production capacity, must be in a long…”
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    Conference Proceeding
  5. 5

    Improving iris image segmentation in unconstrained environments using NMF-based approach by Santoso, Andri, Choirunnisa, Shabrina, Prihasto, Bima, Jia-Ching Wang

    “…Nowadays the segmentation task becomes an important pre-processing stage for the iris classification system. The earlier works in the iris classification field…”
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    Conference Proceeding
  6. 6

    A survey of deep face recognition in the wild by Prihasto, Bima, Choirunnisa, Shabrina, Nurdiansyah, Muhammad Ishak, Mathulaprangsan, Seksan, Chu, Vivian Ching-Mei, Chen, Shi-Huang, Wang, Jia-Ching

    “…Face recognition is one of the significant topics in the biometric security system. This topic has been progressively developed by deep learning approaches,…”
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    Conference Proceeding