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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
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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    Proceeding Paper
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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
    Proposed fatigue index for the objective detection of muscle fatigue using surface electromyography and a double-step binary classifier

    Proposed fatigue index for the objective detection of muscle fatigue using surface electromyography and a double-step binary classifier by Qassim, Hassan M., Hasan, Wan Zuha Wan, Ramli, Hafiz R., Harith, Hazreen Haizi, Inche Mat, Liyana Najwa, Ismail, Luthffi Idzhar

    Published 2022
    “…This paper presents an algorithm that employs a new fatigue index for the objective detection of muscle fatigue using a double-step binary classifier. …”
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  6. 6
    Moving detection using cellular neural network (CNN)

    Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

    Published 2008
    “…Ten images are selected to be used in this project. The algorithm created is used to detect the ball in the images. …”
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    Undergraduates Project Papers
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  7. 7
    Face Detection System / Chan Beh Teng

    Face Detection System / Chan Beh Teng by Chan, Beh Teng

    Published 2004
    “…The system will generate an output where every detected face will be indicated with a rectangle on a copy of the original image. …”
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  8. 8
    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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  9. 9
    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
    “…The use of social media, as well as computational tools and machine learning algorithm, contributes to current public health efforts to detect any indicators of depression from sources close to patients. � 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.…”
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  10. 10
    Image Based Oil Palm Tree Crowns Detection

    Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

    Published 2020
    “…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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    Final Year Project Report / IMRAD
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  11. 11
    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
    “…Location of sources pollution identified and the exact location found at the sensor node number 2 and 4 which indicated by abnormal reading data, various kind of material contained into river detected by the sensors system. …”
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  12. 12
    Image Copy-Move Forgery Detection Algorithms Based on Spatial Feature Domain

    Image Copy-Move Forgery Detection Algorithms Based on Spatial Feature Domain by Ahmed I.T., Hammad B.T., Jamil N.

    Published 2023
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  13. 13
    Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation

    Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

    Published 2000
    “…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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  14. 14
    Analysis of watermarking techniques in video

    Analysis of watermarking techniques in video by Shojanazeri, Hamid, Wan Adnan, Wan Azizun, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Saripan, M. Iqbal

    Published 2011
    “…Thus, research in copyright protection mechanisms, where one of which includes digital watermarking has been receiving an increasing interest from scientists especially in designing a seamless algorithm for effective implementation. Basically digital watermarking involves embedding secret symbols known as watermarks within video data which can be used later for copyright detection purposes. …”
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  15. 15
    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks

    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

    Published 2024
    “…The results of the tests indicated increased performance in terms of fewer false positives, less CPU utilisation, less control channel bandwidth used, higher packet delivery ratio, and fewer flow requests made to the controller with 99.56% detection accuracy as compared to selected benchmarks. …”
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  16. 16
    A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee

    A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

    Published 2023
    “…Therefore, the use of water quality indicators to detect the presence of pollutants is very important. …”
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  17. 17
    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
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  18. 18
    Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical montane forest

    Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta... by Keiko Ioki, Daniel James, Phua, Mui How, Satoshi Tsuyuki, Nobuo Imai

    Published 2022
    “…We also investigated the use of metrics from spectral trajectories of a Landsat time series (LTS) change detection algorithm (LandTrendr) to identify characteristics of disturbance events and their linkage to the recovery of tree community composition, with field validation. …”
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  19. 19
    Incremental learning for large-scale stream data and its application to cybersecurity

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…In the experiment, we study the effect of introducing the outlier detection in RAN-LSH. As a result, by introducing the outlier detection, we confirm that the detection accuracy is enhanced on 377$ 3(53867$.$$1781.8781$0,1$+ average over the testing period. …”
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  20. 20
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The research also develops two new approaches for outlier and potential outlier detection in unimodal and multimodal distributions. …”
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