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  1. 1
    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil

    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil by Idris, Siti Aishah, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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  2. 2
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
    text::Final Year Project
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  3. 3
    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)

    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

    Published 2017
    “…The significant contribution for this study is that the learning rule (e.g. STDP algorithm) has learning capability in memory recall. …”
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    Monograph
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  4. 4
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  5. 5
    Particle swarm optimization with deep learning for human action recognition

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…Motion target detection and tracking are among the most important computer vision areas that use advanced image processing techniques. …”
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  6. 6
    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
    “…Then, various optimized algorithms for the two core processes in the compression, DCT and motion estimation, were reviewed and analyzed. …”
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  7. 7
    The impact of executive function and aerobic exercise recognition in obese children under deep learning

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
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  8. 8
    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood

    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood by Dawood, Farhan

    Published 2015
    “…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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  9. 9
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  10. 10
    Design and performance analysis of artificial neural network for hand motion detection from EMG signals

    Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…The neural network is of backpropagation type, trained by Levenberg-Marquardt training algorithm. Before the classification process, the EMG signals have been pre-processed for extracting some features from them. …”
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  11. 11
    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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  12. 12
    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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  13. 13
    Identification and control of a small-scale helicopter

    Identification and control of a small-scale helicopter by Deboucha, A., Taha, Z.

    Published 2010
    “…This identification process is based on the well-known gradient descent learning algorithm. …”
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  14. 14
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  15. 15
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  16. 16
    A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem

    A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem by Kamal Z., Zamli, Fakhrud, Din, Ahmed, Bestoun S., Bures, Miroslav

    Published 2018
    “…In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). …”
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  17. 17
    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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  18. 18
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  19. 19
    Abnormal event detection in video surveillance / Lim Mei Kuan

    Abnormal event detection in video surveillance / Lim Mei Kuan by Lim, Mei Kuan

    Published 2014
    “…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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  20. 20
    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
    “…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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