Search Results - (( initial detection method algorithm ) OR ( using classification based algorithm ))

Refine Results
  1. 1

    A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

    Published 2022
    “…Once the initial classification is performed using the generalized rules for each test example, the results are validated using the experts feedback. …”
    Get full text
    Get full text
    Article
  3. 3

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
    Get full text
    Get full text
    Conference or Workshop Item
  4. 4
  5. 5

    File integrity monitor scheduling based on file security level classification by Abdullah, Zul Hilmi, Udzir, Nur Izura, Mahmod, Ramlan, Samsudin, Khairulmizam

    Published 2011
    “…The initial testing result shows that our system is effective in on-line detection of file modification.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    Fuzzification of epileptic data: an application for prediction and identification of partial seizure by Malik, Aamir Saeed, Nasif, Mohammad Shakir, Kamel , Nidal, Qidwai, U.

    Published 2013
    “…The paper presents one such technique which is based on fuzzy classifications of the EEG data using certain statistical features from the signal. …”
    Get full text
    Citation Index Journal
  7. 7

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
    Get full text
    Get full text
    Thesis
  8. 8

    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

    Published 2012
    “…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

    Published 2024
    “…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
    Article
  10. 10

    Drone-based surveillance of palm tress ecosystems by Mansor, Ya’akob, Baki, Sharudin Omar, Sahwee, Zulhilmy, Mengyue, Cheng, Wu, Yuanyuan

    Published 2024
    “…The initial phase of the research focuses on elucidating the challenges associated with detecting palm tree health issues using conventional image processing methods in MATLAB. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…Unlike traditional methods that usually start with detection and followed by denoising, the model initially leverages the powerful ability of deep CNN architecture to separate noise from noisy image, then adopts PSO to pinpoint the most optimized threshold values for detecting impulse noisy pixels. …”
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13

    Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

    Published 2020
    “…The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. …”
    Get full text
    Get full text
    Article
  14. 14

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The following results were obtained when classification of the ACS types used the conventional “single AI-basedmethods. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

    Published 2021
    “…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Robust techniques for linear regression with multicollinearity and outliers by Mohammed, Mohammed Abdulhussein

    Published 2016
    “…A new proposed method which is called the modified generalized DFFITS (MGDFF) is developed in this regard, whereby the suspected HLPs in the initial subset are identified using our proposed IDRGP diagnostic method. …”
    Get full text
    Get full text
    Thesis
  17. 17

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
    Get full text
    Get full text
    Book Section
  18. 18

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20

    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

    Published 2024
    “…This scheme incorporates machine learning techniques by utilizing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classification algorithms to accurately identify and handle malicious network traffic following the initial packet filtration process that identifies abnormal traffic. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis