• Login
    View Item 
    •   MBRU Knowledge Repository Home
    • Hamdan Bin Mohammed College of Dental Medicine (HBMCDM)
    • Faculty Publications (HBMCDM)
    • View Item
    •   MBRU Knowledge Repository Home
    • Hamdan Bin Mohammed College of Dental Medicine (HBMCDM)
    • Faculty Publications (HBMCDM)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Improving the accuracy of publicly available search engines in recognizing and classifying dental visual assets using convolutional neural networks

    Thumbnail
    View/Open
    304-2020.50 Ahmed Ghoneima.pdf (617.2Kb)
    Date
    2020
    Author
    Ghoneima, Ahmed
    Metadata
    Show full item record
    Abstract
    Aim: To assess the accuracy of DigiBrain4, Inc (DB4) Dental Classifier and DB4 Smart Search Engine* in recognizing, categorizing, and classifying dental visual assets as compared with Google Search Engine, one of the largest publicly available search engines and the largest data repository. Materials and methods: Dental visual assets were collected and labeled according to type, category, class, and modifiers. These dental visual assets contained radiographs and clinical images of patients’ teeth and occlusion from different angles of view. A modified SqueezeNet architecture was implemented using the TensorFlow r1.10 framework. The model was trained using two NVIDIA Volta graphics processing units (GPUs). A program was built to search Google Images, using Chrome driver (Google web driver) and submit the returned images to the DB4 Dental Classifier and DB4 Smart Search Engine. The categorical accuracy of the DB4 Dental Classifier and DB4 Smart Search Engine in recognizing, categorizing, and classifying dental visual assets was then compared with that of Google Search Engine. Results: The categorical accuracy achieved using the DB4 Smart Search Engine for searching dental visual assets was 0.93, whereas that achieved using Google Search Engine was 0.32. Conclusion: The current DB4 Dental Classifier and DB4 Smart Search Engine application and add-on have proved to be accurate in recognizing, categorizing, and classifying dental visual assets. The search engine was able to label images and reject non-relevant results.
    URI
    https://repository.mbru.ac.ae/handle/1/880
    Collections
    • Faculty Publications (HBMCDM)

    Related items

    Showing items related by title, author, creator and subject.

    • Children’s dental anxiety (self and proxy reported) and its association with dental behaviour in a postgraduate dental hospital 

      AlGharebi, S.; Al‑Halabi, M.; Mawlood, K.; Khamis, AH; Hussein, I (2020)
      Purpose: Child dental anxiety (CDA) and uncooperative dental behaviour are common. We aimed to assess the prevalence of CDA (self- and proxy- reported) in the United Arab Emirates (UAE) children related to their dental ...
    • Correction to: Children’s dental anxiety (self and proxy reported) and its association with dental behaviour in a postgraduate dental hospital 

      Algharebi, Safeya; Al-Halabi, Manal; Kowash, Mawlood B.; Khamis, Amar; Hussein, Iyad (2020)
      Correction to: European Archives of Paediatric Dentistry: https ://doi.org/10.1007/s4036 8-020-00517 -x In the original publication of the article the third author’s name “M. Kowash” was submitted as “K. Mawlood” which ...
    • UAE Children’s Dental Anxiety (Self and Proxy Reported) and their Dental Behavior 

      Algharebi, Safeya (2019-08)
      Background: Child dental anxiety and uncooperative behavior in dental practice are common and intertwined. Aim: To assessthe prevalence of dental anxiety (self and proxy reported) in a subgroup of 7–16-year-oldchildrenand ...

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of MBRU Knowledge RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV