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  1. 1
    AR oriented pose matching mechanism from motion capture data

    AR oriented pose matching mechanism from motion capture data by Iqbal J., Sidhu M.S., Ariff M.B.M.

    Published 2023
    “…In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). …”
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  2. 2
    Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language

    Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language by Sutarman, .

    Published 2016
    “…The sample of 3D data coordinates of X, Y, and Z axis is a value relative to the torso and head. In this study, the images has been captured using a kinect sensor based skeletal algorithms. …”
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  3. 3
    HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM

    HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM by LO , TIMOTHY YIN HONG

    Published 2019
    “…A video sequence consists of sequences of frame, with the detection algorithm, these frames can be analyzed and detect any” “abnormal behavior such as crime.” …”
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    Final Year Project
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  4. 4
    Vision-Based Autonomous Vehicle Driving Control System

    Vision-Based Autonomous Vehicle Driving Control System by Isa, Khalid

    Published 2005
    “…In this subsystem, image-capturing techniques capture the video images frame by frame. After that, lane detection process extracts the information about vehicle position with respect to the highway lane. …”
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  5. 5
    Vision-based autonomous vehicle driving control system

    Vision-based autonomous vehicle driving control system by Isa, Khalid

    Published 2005
    “…In this subsystem, image-capturing techniques capture the video images frame by frame. After that, lane detection process extracts the information about vehicle position with respect to the highway lane. …”
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  6. 6
    Slam-based mapping for object recognition

    Slam-based mapping for object recognition by Loh, Wan Ying

    Published 2018
    “…The SIFT (Scale-Invariant Feature Transform) is used to extract features from the current frame and match with the object database to identify and recognize the object whenever the robot come across the object. …”
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  7. 7
    An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM classifier

    An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM... by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

    Published 2021
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  8. 8
    A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow

    A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow by Harold Harrison, Mazlina Mamat, Farah Wong, Hoe Tung Yew, Racheal Lim, Wan Mimi Diyana Wan Zaki

    Published 2025
    “…Techniques such as Region of Interest (ROI) cropping and multi-section frame extraction were implemented to reduce computational complexity while further enhancing accuracy. …”
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  9. 9
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  10. 10
    A block cipher based on genetic algorithm

    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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  11. 11
    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources

    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources by Al-Qadhi, Abdulrahman K., Athauda, Rukshan, Latip, Rohaya, Hussin, Masnida

    Published 2026
    “…We have evaluated the FaaSBid model and the proposed algorithms and pricing model by comparing with a number of existing models and algorithms using real-world datasets. …”
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  12. 12
    Analysis of performance between kinect v1 and kinect v2 for various facial part movements

    Analysis of performance between kinect v1 and kinect v2 for various facial part movements by Heng, Sheng Guang, Rosdiyana, Samad, Mahfuzah, Mustafa, Nor Rul Hasma, Abdullah, Pebrianti, Dwi

    Published 2019
    “…A total number of 18 desired facial feature point at similar landmarks will be extracted in the format of 3D coordinates for both Kinect cameras. …”
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  13. 13
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  14. 14
    Computing the autopilot control algorithm using predictive functional control for unstable model

    Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

    Published 2009
    “…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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  15. 15
    Design and implementation of MD5 hash function algorithm using verilog HDL

    Design and implementation of MD5 hash function algorithm using verilog HDL by Shamsiah, Suhaili, Niam, Cleopatra Chundang, Zainah, Md Zain, Norhuzaimin, Julai

    Published 2022
    “…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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  16. 16
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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  17. 17
    A-star (A*) algorithm implementation for robotics path planning navigation

    A-star (A*) algorithm implementation for robotics path planning navigation by Emirul Ridzwan, Nor Azmi

    Published 2018
    “…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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  18. 18
    Design and Implementation of MDS Hash Function Algorithm Using Verilog HDL

    Design and Implementation of MDS Hash Function Algorithm Using Verilog HDL by Shamsiah, Suhaili, Cleopatra Chundang, Niam, Zainah, Md. Zain, Norhuzaimin, Julai

    Published 2020
    “…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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  19. 19
    An efficient computation technique for cryptosystems based on Lucas functions

    An efficient computation technique for cryptosystems based on Lucas functions by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

    Published 2008
    “…We have found that the binary sequence used in a new algorithm is shorter than a special sequence used in an existing algorithm. …”
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  20. 20
    A video-rate color image segmentation using adaptive and statistical membership function

    A video-rate color image segmentation using adaptive and statistical membership function by Sojodishijani, Omid, Rostami, Vahid, Ramli, Abdul Rahman

    Published 2010
    “…In this algorithm, statistical information of regions is used to create fuzzy membership functions in color model components. …”
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