Search Results - (( java application path algorithm ) OR ( automatic identification rules algorithm ))

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  1. 1
    Feature extraction using spectral centroid and mel frequency cepstral coefficient for Quranic accent automatic identification

    Feature extraction using spectral centroid and mel frequency cepstral coefficient for Quranic accent automatic identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Nematollahi, Mohammad Ali, Hassan, Abd Rauf

    Published 2014
    “…This paper presents the process of Quranic Accent Automatic Identification. Recent feature extraction technique that is used for Quranic verse rule identification/Tajweed include Mel Frequency Cepstral Coefficients (MFCC) which prone to additive noise and may reduce the classification result. …”
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  2. 2
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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    Thesis
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  3. 3
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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    Final Year Project / Dissertation / Thesis
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  4. 4
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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  5. 5
    Fuzzy modelling using firefly algorithm for phishing detection

    Fuzzy modelling using firefly algorithm for phishing detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Shahreen, Kasim, Mohd Saberi, Mohamad, Ashraf Osman, Ibrahim

    Published 2019
    “…To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). …”
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  6. 6
    Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control

    Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control by Mohd. Noor, Nurul Muthmainnah, Ahmad, Salmiah

    Published 2015
    “…Since membership functions (MFs) are generated automatically, the proposed fuzzy learning algorithm can be viewed as a knowledge acquisition tool for classification problems. …”
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  7. 7
    Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image

    Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

    Published 2016
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  8. 8
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

    Published 2012
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc.This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism.A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism.The English corpus is the translated version of the Malay corpus.Hence, these two corpora are treated as parallel corpora. …”
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  9. 9
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism. A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism. …”
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  10. 10
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism. A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism. …”
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  11. 11
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism. A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism. …”
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  12. 12
    Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques

    Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques by Mohammed, Mazin Abed, Mohd Khanapi, Abd Ghani, M.A., Burhanuddin, Arunkumar, N., Mostafa, Salama A., Ibrahim, Dheyaa Ahmed, Abdullah, Mohamad Khir, Jaber, Mustafa Musa, Abdulhay, Enas, Ramirez-Gonzalez, Gustavo

    Published 2020
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