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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  5. 5
    Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches

    Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches by Latif S.D., Alyaa Binti Hazrin N., Hoon Koo C., Lin Ng J., Chaplot B., Feng Huang Y., El-Shafie A., Najah Ahmed A.

    Published 2024
    “…Statistical models and machine learning algorithms automatically learn and improve based on data. …”
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  6. 6
    The operational role of remote sensing in assessing and predicting land use/land cover and seasonal land surface temperature using machine learning algorithms in Rajshahi, Bangladesh

    The operational role of remote sensing in assessing and predicting land use/land cover and seasonal land surface temperature using machine learning algorithms in Rajshahi, Bangladesh by Zullyadini A. Rahaman

    Published 2021
    “…The operational role of remote sensing in assessing and predicting land use/land cover and seasonal land surface temperature using machine learning algorithms in Rajshahi, Bangladesh by Zullyadini A. …”
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  7. 7
    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar

    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

    Published 2020
    “…Thus, by enhancing the classification techniques in OBIA, building extraction accuracy using ML algorithms for medium resolution images can be improved and the expenses also can be reduced indirectly.…”
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  8. 8
    Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain

    Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain by Mohammad Asif , Hossain

    Published 2022
    “…The selection would be made based on the hybrid machine learning (ML) algorithm. A fuzzy-based Naive Bayes algorithm has been used in this case. …”
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  9. 9
    Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data

    Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data by Kalantar, Bahareh, Ueda, Naonori, Saeidi, Vahideh, Ahmadi, Kourosh, Abdul Halin, Alfian, Shabani, Farzin

    Published 2020
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  10. 10
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
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  11. 11
    Feedforward neural network for solving particular fractional differential equations

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…This study also focuses on solving fractal-fractional differential equations in the Caputo sense with a power-law kernel (FFDEsCP) using FNN in two hidden layers with a vectorized algorithm alongside Adam (FNN2HLVA-Adam). …”
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  12. 12
    Calibration of optical based silicone tactile sensor based on image deformation technique / Abdul Halim Esa

    Calibration of optical based silicone tactile sensor based on image deformation technique / Abdul Halim Esa by Esa, Abdul Halim

    Published 2016
    “…Object profile surface and shape can also be determined. By using tactile sensor, the robot fingers tip, condition monitoring machine and object manipulation task system adopted to the environment by sense of touch. …”
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  13. 13
    Semantic relatedness maximisation for word sense disambiguation using a hybrid firefly algorithm

    Semantic relatedness maximisation for word sense disambiguation using a hybrid firefly algorithm by Hamad, A.H., Mahmood, A.A., Abed, S.A., Ying, X.

    Published 2021
    “…Word sense disambiguation (WSD) refers to determining the right meaning of a vague word using its context. …”
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  14. 14
    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms

    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

    Published 2020
    “…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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  15. 15
    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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  16. 16
    Support vector classification of remote sensing images using improved spectral Kernels

    Support vector classification of remote sensing images using improved spectral Kernels by Md. Sap, Mohd. Noor, Kohram, Mojtaba

    Published 2008
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  17. 17
    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail

    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Building is one of the major features that available on the land used on the earth especially in urban area. By using remote sensing method, it can reduce time to collect data for a large area. …”
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  18. 18
    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
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  19. 19
    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

    Published 2021
    “…Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. …”
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  20. 20
    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine

    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine by Farah Nuralissa Muhammad, Lam, Kuok Choy

    Published 2023
    “…The accuracy assessment test using the Kappa coefficient resulted in a value of 0.7893 for the RF algorithm and 0.6328 for the SVM algorithm for the year 2010. …”
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