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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. …”
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  3. 3
    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system

    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

    Published 2018
    “…Our propose model has been apple based as intrusion detection and validated based on NSL-KDD data set. …”
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  4. 4
    Forgery detection in medical images using Complex Valued Neural Network (CVNN)

    Forgery detection in medical images using Complex Valued Neural Network (CVNN) by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Zeki, Akram M., Aburas, Abdurazzag Ali

    Published 2011
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  5. 5
    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory

    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory by Rusli, Julie Roslita

    Published 2011
    “…Three types of March algorithms which are March 17N, March 12N and MarchPS 23N are selected to validate the tool in term of their compatibility for NPSF detection and diagnosis.Suitable data background is identified and a test procedure is developed for each algorithm. …”
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  6. 6
    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…Prior to localization of the base of young corn tree, skeletonizing operation is performed to get the basic shape of the object. Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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  7. 7
    Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model

    Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model by Sulaiman , Marizan, Adnan, Tawafan, Ibrahim, Zulkifilie

    Published 2013
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  8. 8
    Using text mining algorithm to detect gender deception based on Malaysian chat room lingo / Dianne L. M. Cheong and Nur Atiqah Sia Abdullah @ Sia Sze Yieng

    Using text mining algorithm to detect gender deception based on Malaysian chat room lingo / Dianne L. M. Cheong and Nur Atiqah Sia Abdullah @ Sia Sze Yieng by Cheong, Dianne L.M., Sia Abdullah, Nur Atiqah

    Published 2006
    “…Inference can be made both from writing style and from clues hidden in the posting data. A text-mining algorithm was designed to detect gender deception based on gender-preferential features at the word or clause level of Malaysian e-mail users. …”
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  9. 9
    A real-time vision-based touchless interaction of virtual heart using integration of motion gesture interaction methods

    A real-time vision-based touchless interaction of virtual heart using integration of motion gesture interaction methods by Ng, Ing Kye

    Published 2014
    “…Third, the range which is defined as left or right is used for gesture recognition. Lastly, the basic transformation such as rotation, translation and scale is executed if a data motion lies within the range. …”
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  10. 10
    Using text mining algorithm to detect gender deception based on Malaysian chatroom lingo / Dianne L.M. Cheong and Nur Atiqah Sia Abdullah@Sia Sze Yieng

    Using text mining algorithm to detect gender deception based on Malaysian chatroom lingo / Dianne L.M. Cheong and Nur Atiqah Sia Abdullah@Sia Sze Yieng by L., Dianne M. Cheong, Sia Abdullah, Nur Atiqah

    Published 2006
    “…Based on this designed text algorithm, a prototype in Visual Basic is developed. …”
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    Research Reports
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  11. 11
    An ensemble feature selection method to detect web spam

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…Web spam detection is one of research fields of data mining. …”
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  12. 12
    Water Pollution Source Identification Based on Real-Time Monitoring System in Siak River

    Water Pollution Source Identification Based on Real-Time Monitoring System in Siak River by Kadir, E.A., Listia Rosa, S., Othman, M.

    Published 2021
    “…Data collected from the sensor analyzed use algorithm to find and check the abnormal and behavior data changing by the time. …”
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  13. 13
    Medical diagnosis using data mining techniques / Shaiful Nizam Zamri

    Medical diagnosis using data mining techniques / Shaiful Nizam Zamri by Shaiful Nizam , Zamri

    Published 2003
    “…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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  14. 14
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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  15. 15
    Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review

    Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review by Mat Ripah N.A., Abdul Latif A., Che Cob Z., Mohd Drus S., Md Anwar R., Mohd Radzi H.

    Published 2024
    “…This SLR discovered that the chosen social media data is basically the country's leading social site. …”
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  16. 16
    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer

    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

    Published 2023
    “…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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  17. 17
    Earthquake location detector system (ELDS)

    Earthquake location detector system (ELDS) by Surwindraj Ang Soon Lee

    Published 2024
    text::Final Year Project
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  18. 18
    Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach

    Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin, Rangkuti, Chalillullah

    Published 2010
    “…Structure and network weights for the NF model are determined by a synergetic approach – Data clustering and Gradient Descent algorithm. Operation data collected in 10 seconds interval and for one day is used for model training and validation. …”
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  19. 19
    Human Spontaneous Emotion Detection System

    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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  20. 20
    Image Splicing Detection With Constrained Convolutional Neural Network

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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