Search Results - (( knowledge visualization using algorithm ) OR ( learning application interface algorithm ))

Refine Results
  1. 1

    Translating medical image to radiological report: Adaptive multilevel multi-attention approach by Gajbhiye, G.O., Nandedkar, A.V., Faye, I.

    Published 2022
    “…The results of language generation metrics for proposed variants were acquired using the COCO-caption evaluation Application Program Interface (API). …”
    Get full text
    Get full text
    Article
  2. 2

    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension by Affandy

    Published 2015
    “…This model is then to be used in the prototype tool development that is called 3De-ALPROV (Design Development Debug – Algorithm Program Visualization). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

    A Machine Learning Classification Application to Identify Inefficient Novice Programmers by Khan I., Al-Mamari A., Al-Abdulsalam B., Al-Abdulsalam F., Al-Khansuri M., Iqbal Malik S., Ahmad A.R.

    Published 2023
    “…Data mining; Graphical user interfaces; Learning algorithms; Machine learning; Nearest neighbor search; Academic performance; Application layers; Computer science students; Educational data mining; Educational Institutes; K-near neighbor; Machine learning classification; Nearest-neighbour; Novice programmer; Productive tools; Students…”
    Conference Paper
  8. 8
  9. 9
  10. 10

    Thalassaemia detection using CBR Algorithm via mobile device by Nur Faezah, Omar

    Published 2011
    “…Moreover,this application will be using the programming language Visual Basic. Net applied in Visual Studio 2008.The methodology has chosen is rapid application development (RAD) where this method is the archive with apparel search requirement. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  11. 11

    Thalassaemia detection using CBR Algorithm via mobile device by Nur Faezah, Omar

    Published 2011
    “…Moreover,this application will be using the programming language Visual Basic. Net applied in Visual Studio 2008.The methodology has chosen is rapid application development (RAD) where this method is the archive with apparel search requirement. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  12. 12

    Fast Corner Detection in Augmented Reality Learning Management of the Corpse by Undang, Syaripudin, Diena Rauda, Ramdania, Wine, Widiawaty, Wildan Budiawan, Zulfikar, Dian Sa'adillah, Maylawati

    Published 2021
    “…The application also meets 82.8% of the user side's usability level, which indicates that this application is beneficial for learning. …”
    Get full text
    Get full text
    Get full text
    Journal
  13. 13

    Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

    Published 2024
    “…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18

    NLP- based for providing mental health support in mobile application / Muhammad Amirul Roslan by Roslan, Muhammad Amirul

    Published 2025
    “…Future enhancements, such as advanced machine learning algorithms and user interface improvements, are proposed to further enhance functionality. …”
    Get full text
    Get full text
    Thesis
  19. 19

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The implementation of parallel algorithm based on parallel computing system is used to visualize the growth of human tumour. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  20. 20

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”
    Proceedings Paper