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  1. 1

    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
    “…In the most predictive application, Backpropagation (BP) has been used to learn the behavioural motion pattern. In terms of plausibility, BP has several drawbacks due to the lack in functionalities in complex data (e.g. spatio-temporal data). …”
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    Monograph
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    Motion learning using spatio-temporal neural network by Yusoff, Nooraini, Ahmad, Farzana Kabir, Jemili, Mohamad Farif

    Published 2020
    “…In this study, learning is implemented on a reward basis without the need for learning targets.The algorithm has shown good potential in learning motion trajectory particularly in noisy and dynamic settings. …”
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    Article
  4. 4

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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    Thesis
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    Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control by Mohd. Noor, Nurul Muthmainnah, Ahmad, Salmiah

    Published 2015
    “…In this paper, the fuzzy-based classifiers were designed in order to determine the eye movement data. These data were used as an input reference in wheelchair motion control. …”
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    Article
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    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…Third, to propose orientation invariant based deep spare autoencoder methods for automatic complex activity identification to minimize orientation inconsistencies and learn adequate data patterns. Furthermore, to confirm the performances of the proposed multi-sensor fusion methods using challenging motion sensor data generated using smartphones and wearable sensors. …”
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    Thesis
  7. 7

    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. As a case study, the multiple-input multiple-output (MIMO) model predictive control (MPC) is applied to control the pitch motion of the helicopter. …”
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    Article
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    Immersive AR pet game with hand motion by Chong, Jing Voon

    Published 2023
    “…Unity provides a cross-platform development environment for AR applications that run on different devices with varying capabilities. ManoMotion is a hand-tracking software that uses machine learning algorithms to track and recognise hand movements in real-time. …”
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    Final Year Project / Dissertation / Thesis
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    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…It is proposed and shown that route-like intelligent motion is based on a combination of decisional and kinematical factors. …”
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    Thesis
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    An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems by Haneen, Abd Wahab, Noraziah, Ahmad, Alsewari, Abdulrahman A., Sinan, Q. Salih

    Published 2019
    “…Additionally, LBH is then tested using six real datasets available from UCI machine learning laboratory. The experimental outcomes obtained indicated the designed algorithm’s suitability for data clustering, displaying effectiveness and robustness.…”
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    Article
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    Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security by Pitafi, S., Anwar, T., Dewa Made Widia, I., Yimwadsana, B.

    Published 2023
    “…To solve the above problem, we designed a prototype for PIDS using a DHT22 temperature and humidity sensor, vibration sensor SW- 420 Module Pinout, Mini PIR motion sensor, and Arduino UNO. After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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    Article
  13. 13

    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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    Thesis
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    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Data clustering is one of the most popular branches in machine learning and data analysis. …”
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    Thesis
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    An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

    Published 2019
    “…Additionally, LBH is then tested using six real datasets available from UCI machine learning laboratory. The experimental outcomes obtained indicated the designed algorithm's suitability for data clustering, displaying effectiveness and robustness.…”
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    Article
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    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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    Conference or Workshop Item
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    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…Although motor imagery signals have been used in assisting the hand grasping motion amongst others motions, nonetheless, such signals are often difficult to be generated. …”
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    Thesis
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    Motion Capture Technologies for Ergonomics: A Systematic Literature Review by Salisu, S., Ruhaiyem, N.I.R., Eisa, T.A.E., Nasser, M., Saeed, F., Younis, H.A.

    Published 2023
    “…A medical diagnosis using AI applies machine learning algorithms and motion capture technologies to analyze patient data, enhancing diagnostic accuracy, enabling early disease detection and facilitating personalized treatment plans. …”
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    Article
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    Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

    Published 2022
    “…To identify complicated human behaviors, deep learning approaches are more suited since they can automatically learn the features from the data. …”
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    Proceeding