Search Results - (( vr application based algorithm ) OR ( its application means algorithm ))

Refine Results
  1. 1
  2. 2

    REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

    Published 2006
    “…Apparently, latency is one of the most frequently cited shortcomings of current Virtual Reality (VR) applications. To compensate latency, previous prediction mechanisms insert a complex mathematical algorithm, which may not be appropriate for complex virtual training applications. …”
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Enhancing unity-based AR with optimal lossless compression for digital twin assets by Hlayel, Mohammed, Hairulnizam, Mahdin, Hayajneh, Mohammad, AlDaajeh, Saleh H., Siti Salwani, Yaacob, Mazidah, Mat Rejab

    Published 2024
    “…Brotli emerged as a strong option for web-based AR/VR content, striking a balance between compression efficiency and decompression speed, outperforming Gzip in WebGL contexts. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5
  6. 6
  7. 7

    Eye fixation versus pupil diameter as eye- tracking features for virtual reality emotion classification by Lim Jia Zheng, James Mountstephens, Jason Teo

    Published 2022
    “…In this study, an empirical comparison of the accuracy of eye-tracking-based emotion recognition in a virtual reality (VR) environment using eye fixation versus pupil diameter as the classification feature is performed. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
  8. 8

    Real-time robotic avatar control using fuzzy gaze-classification for people with disability by Qidwai, U., Shakir, M., Bahameish, M.

    Published 2016
    “…The presented solution incorporates Optical Gaze System, within a Virtual reality (VR) headset to control a robotic Avatar remotely based on the gaze position. …”
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9
  10. 10

    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering by Hengda, Wang, Mohamad Mohsin, Mohamad Farhan, Mohd Pozi, Muhammad Syafiq

    Published 2024
    “…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
    Get full text
    Get full text
    Thesis
  16. 16

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  17. 17
  18. 18
  19. 19

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
    Get full text
    Get full text
    Final Year Project
  20. 20

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
    Get full text
    Get full text
    Final Year Project