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  1. 1
    Confidentiality Based Data Classification Using Sematic-K-NN Algorithm in Cloud Virtual Enviroment

    Confidentiality Based Data Classification Using Sematic-K-NN Algorithm in Cloud Virtual Enviroment by Ali, Munwar

    Published 2016
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  2. 2
    Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khairan Mohd Asri

    Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair... by Mohd Asri, Mohamad Khairan

    Published 2023
    “…Two algorithms, the Cloth Simulation Filter (CSF) in CloudCompare and the Multiscale Curvature Classification (MCC) in Global Mapper, were tested for this purpose. …”
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  3. 3
    Data classification based on confidentiality in virtual cloud environment

    Data classification based on confidentiality in virtual cloud environment by Zardari, M.A., Jung, L.T., Zakaria, M.N.B.

    Published 2014
    “…In this study, we have proposed a data classification cloud model to solve data confidentiality issue in cloud computing environment. …”
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  4. 4
    K-NN classifier for data confidentiality in cloud computing

    K-NN classifier for data confidentiality in cloud computing by Zardari, M.A., Jung, L.T., Zakaria, N.

    Published 2014
    “…K-NN data classification technique is modulated in the cloud virtual environment. …”
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  5. 5
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  6. 6
    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm

    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

    Published 2024
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  7. 7
    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing

    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing by Alsaaidah, Yousef A., Muhammed, Abdullah, Ala’anzy, Mohammed Alaa, Othman, Mohamed, Abdullah, Azizol

    Published 2025
    “…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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  8. 8
    Load balancing and server consolidation in cloud computing environments: a meta-study

    Load balancing and server consolidation in cloud computing environments: a meta-study by Fadhil, Mohammed Alaa, Othman, Mohamed

    Published 2019
    “…The data-center is considered the heart of cloud computing. …”
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  9. 9
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
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  10. 10
    Diagnosis security problems in cloud computing for business cloud

    Diagnosis security problems in cloud computing for business cloud by Shakir M., Abubakar A.B., Yousoff Y.B., Sagher A.M., Alkayali H.

    Published 2023
    “…Cloud computing features ease, fast accessibility of the data and cost reduction for data storage. …”
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  11. 11
    A refined classification approach by integrating Landsat Operational Land Imager (OLI) and RADARSAT-2 imagery for land-use and land-cover mapping in a tropical area

    A refined classification approach by integrating Landsat Operational Land Imager (OLI) and RADARSAT-2 imagery for land-use and land-cover mapping in a tropical area by Sameen, Maher Ibrahim, Nahhas, Faten Hamed, Buraihi, Faez Hussein, Pradhan, Biswajeet, Mohamed Shariff, Abdul Rashid

    Published 2016
    “…Different classification algorithms were adopted to classify the integrated Landsat and SAR data, and the maximum likelihood classifier (MLC) was considered the best approach. …”
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  12. 12
    Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.

    Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh. by Omar, Saodah, Isa, Iza Sazanita, Mohd Saleh, Junita

    Published 2010
    “…An Artificial Neural Network (ANN) system has been extensively applied to numerous data classification problems such as cloud classification, business applications (sales forecasting), and medical domain for clinical diagnosis. …”
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    Research Reports
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  13. 13
    Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud

    Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud by Mohd Romlay, Muhammad Rabani, Mohd Ibrahim, Azhar, Toha, Siti Fauziah, De Wilde, Philippe, Venkat, Ibrahim

    Published 2021
    “…Therefore, a classification method which could receive sparse input, while providing ample leverage for the classification process to accurately differentiate objects within limited computing capability is required. …”
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  14. 14
    Imaging spectroscopy and light detection and ranging data fusion for urban features extraction

    Imaging spectroscopy and light detection and ranging data fusion for urban features extraction by Idrees, Mohammed, Mohd Shafri, Helmi Zulhaidi, Saeidi, Vahideh

    Published 2013
    “…The composite image was classified using unsupervised classification (k-mean algorithm) and the accuracy of the classification assessed. …”
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  15. 15
    Mapping the spatial distribution and changes of oil palm land cover using an open source cloud-based mapping platform

    Mapping the spatial distribution and changes of oil palm land cover using an open source cloud-based mapping platform by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Prince, Husni Mobarak, Yusuf, Badronnisa, Hamud, Ahmed Mohamed

    Published 2019
    “…The Remote Ecosystem Monitoring Assessment Pipeline (REMAP) provides a cloud computing platform that hosts an open-source stacked Landsat data that allows land cover classification to be implemented using a built-in random forest supervised machine learning algorithm. …”
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  16. 16
    A Review on Data Stream Classification

    A Review on Data Stream Classification by A. A., Haneen, Noraziah, Ahmad, Mohd Helmy, Abd Wahab

    Published 2018
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  17. 17
    Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin

    Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin by Sharuddin, Nurul Ain Nabilah

    Published 2022
    “…Recent developments in big data and cloud computing enable quick mapping on a wide scale. …”
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  18. 18
    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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  19. 19
    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation

    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.

    Published 2025
    “…Conventional LULC mapping faces challenges in capturing changes under cloud cover and limited ground truth data. To enhance the accuracy and comprehensiveness of the descriptions of LULC changes, this investigation employed a combination of advanced techniques. …”
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  20. 20
    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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