Search Results - (( parameter classification using algorithm ) OR ( _ visualization using algorithm ))

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  1. 1

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  2. 2

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  3. 3

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…The first algorithm locates interest points in food images using an MSER. …”
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    Thesis
  4. 4

    Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

    Published 2021
    “…UECFOOD-100 and UNICT-FD1200 are the two food datasets used to benchmark the proposed algorithm. The results of this research have found that the ERS algorithm by using optimum parameters and thresholds, be able to reduce the number of extremal regions with sustained classification performance.…”
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    Article
  5. 5

    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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    Thesis
  6. 6

    Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks by Al-Asaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

    Published 2025
    “…Despite the growing use of MHAs, existing studies often focus on specific subsets of algorithms or narrow application domains, leaving a gap in understanding their comprehensive potential and comparative performance across diverse classification tasks. …”
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    Article
  7. 7

    Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

    Published 2021
    “…UECFOOD-100 and UNICT-FD1200 are the two food datasets used to benchmark the proposed algorithm. The results of this research have found that the ERS algorithm by using optimum parameters and thresholds, be able to reduce the number of extremal regions with sustained classification performance.…”
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    Article
  8. 8

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
  9. 9

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…These methods present a robust system that enables fully automated identification and removal of artifacts from EEG signals, without the need of visual inspection or arbitrary thresholding. The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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    Thesis
  10. 10

    The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

    Published 2023
    “…However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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    Thesis
  11. 11

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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    Article
  12. 12

    Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

    Published 2024
    “…We applied these algorithms on their datasets using its GUI or command-line parameters. …”
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    Conference or Workshop Item
  13. 13

    Development Of Vehicle Tracking And Counting System From Traffic Surveillance Video by Kueh , Chiung Lin

    Published 2015
    “…Simple tracking and counting algorithm is used to track and count the detected vehicle. …”
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    Thesis
  14. 14

    Expression invariant face recognition using multi-stage 3D face fitting with 3D morphable face model by Alomari, Abdallah A., Khalid, Fatimah, O. K. Rahmat, Rahmita Wirza, Abdullah, Muhamad Taufik

    Published 2010
    “…This 3D morphable model algorithm can be widely used for 3D face analysis and 3D face recognition in real time scenarios.…”
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    Conference or Workshop Item
  15. 15
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    Processing and classification of landsat and sentinel images for oil palm plantation detection by Mohd Ibrahim, Azhar, Asming, Muhammad Anwar Azizan, Abir, Intiaz Mohammad

    Published 2022
    “…The parameters for ANN were later adjusted to identify the best ANN classification, resulting in an overall accuracy of 98.2857% and 0.9792 of kappa coefficient, and manages to effectively detect oil palm trees from the background.…”
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    Article
  17. 17

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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    Thesis
  18. 18

    Development of computer aided design system based on artificial neural network for macular hole detection by Jayapalan, Mohana Phriya

    Published 2021
    “…There are browse image, pre-processing, segmentation, feature extraction and lastly classification steps. This study successfully classified the Macular Hole and normal retinal images correctly using Artificial Neural Network (ANN) classification. …”
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    Thesis
  19. 19

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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    Article
  20. 20

    Knowledge Discovery Of Noise Level In Lecture Rooms by Tang, Jau Hoong

    Published 2018
    “…Recorded audio data will go through data pre-processing for outlier and extreme value screening. Data classification was conducted in two phases; initially on 23 built-in classifier algorithms followed by a refinement of seven better-performed classifiers with selective attributes investigation using Weka tool. …”
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    Monograph