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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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    Thesis
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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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    Book
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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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  4. 4
    Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset

    Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset by Chew, Chin Boon

    Published 2018
    “…The segmentation results from the algorithm developed are competitive. However, improvements still can be made.…”
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    Monograph
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  5. 5
    Adaptive mesh refinement immersed boundary method for simulations of laminar flows past a moving thin elastic structure

    Adaptive mesh refinement immersed boundary method for simulations of laminar flows past a moving thin elastic structure by Aldlemy, M.S., Rasani, M.R., Ariffin, A.K., Ya, T.M.Y.S.T.

    Published 2020
    “…In this algorithm, adaptive mesh refinement (AMR) is integrated with immersed boundary finite element method (IBFEM) with two-stage pressure-velocity corrections. …”
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  6. 6
    Towards a unified image quality assessment technique for cross-content image processing applications

    Towards a unified image quality assessment technique for cross-content image processing applications by Baqar, Mohtashim *

    Published 2024
    “…In summary, the study develops algorithms for accurate image quality prediction, refining images, and enhancing visual quality. …”
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  7. 7
    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil

    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…Future work entails enhancing system robustness through comprehensive contingency planning, real-time data integration, and algorithmic optimization, with a focus on refining the genetic algorithm and exploring parallel processing techniques to further enhance efficiency and scalability.…”
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  8. 8
    Refinement of generated weighted fuzzy production rules by using fuzzy neural networks for stock market prediction.

    Refinement of generated weighted fuzzy production rules by using fuzzy neural networks for stock market prediction. by Md. Sap, Mohd. Noor, Khokar, Rashid Hafeez

    Published 2005
    “…In this paper, we look into the solutions of the above problems by 1) enhancing the representation power of WFPRs by including local and global weights, 2) developing a fuzzy neural network (FNN) with enhanced learning algorithm, and 3) using this FNN to refine the local and global weights of WFPRs for stock market prediction. …”
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  9. 9
    Local Stereo Matching Algorithm Using Modified Dynamic Cost Computation

    Local Stereo Matching Algorithm Using Modified Dynamic Cost Computation by Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Abd Manap, Nurulfajar, Hamid, Mohd Saad, Tg. Wook, Tg Mohd Faizal

    Published 2021
    “…This work improves the local method stereo matching algorithm based on the dynamic cost computation method for depth measurement. …”
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  10. 10
    Refined adaptive video quality demands over heterogeneous networks

    Refined adaptive video quality demands over heterogeneous networks by Issa, Sinzobakwira, Khalifa, Othman Omran, Gunawan, Teddy Surya

    Published 2017
    “…With current portable devices, users change dynamically their positions and demands, thus anticipating the distribution methods of bandwidths and channel capacities. Two modules are used to perform the quality adaptation: the First Adaptive Video Quality (FAVQ) and the Refined Adaptive Video Quality (RAVQ). …”
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  11. 11
    Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image

    Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image by Zainal Azali, Muhammad Nazmi

    Published 2024
    “…The algorithm development can be categorized into local, global, and semi-global methods. …”
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  12. 12
    Development of obstable avoidance system for 3D robot navigation

    Development of obstable avoidance system for 3D robot navigation by Er, Kai Sheng

    Published 2024
    “…In this project, an algorithm was developed to implement an obstacle avoidance system in 3D robot navigation. …”
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    Final Year Project / Dissertation / Thesis
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  13. 13
    Windows-Based bandwidth allocation on optical networks

    Windows-Based bandwidth allocation on optical networks by Mahadevan, V., Yu, W., Zhou, J.

    Published 2009
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  14. 14
    Facial features for template matching based face recognition

    Facial features for template matching based face recognition by Chai, Tong Yuen, Mohd Rizon, Mohamed Juhari, Prof. Dr., Woo, San San, Tan, Ching Seong, Dr.

    Published 2011
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  15. 15
    Face recognition using eigenfaces and smooth support vector machine

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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  16. 16
    Face recognition using eigenfaces and smooth support vector machine

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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    Undergraduates Project Papers
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  17. 17
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…Furthermore, colour threshold analysis and edge detection algorithms are redesigned exclusively to refine the two-dimensional coefficients into a more meaningful low-level representation. …”
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  18. 18
    Routing problem in rectangular mesh network using Dijkstra’s based Greedy method

    Routing problem in rectangular mesh network using Dijkstra’s based Greedy method by Noraziah, Adzhar, Shaharuddin, Salleh, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2018
    “…This paper presents a complete routing algorithm which can further refine the solution by using Dijkstra’s based greedy method. …”
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  19. 19
    Routing problem in rectangular mesh network using shortest path based Greedy method

    Routing problem in rectangular mesh network using shortest path based Greedy method by Noraziah, Adzhar, Shaharuddin, Salleh, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2019
    “…This paper presents a complete routing algorithm which can further refine the solution by using Dijkstra's based greedy method. …”
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  20. 20
    Fireflyclust: an automated hierarchical text clustering approach

    Fireflyclust: an automated hierarchical text clustering approach by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2017
    “…The proposed clustering method operates based on five phases: data pre-processing, clustering, item re-location, cluster selection and cluster refinement. …”
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