Search Results - (( data classification using algorithm ) OR ( parameter extraction using algorithm ))

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  1. 1
    An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin

    An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

    Published 2022
    “…There are 6 different ways of designing the experiment to evaluate the result of the study, which are an experiment with the model using different stemming techniques, an experiment with the model using three different algorithms, the result analysis of confusion matric of three algorithms, experiment the model using different SVM kernel, experiment the model using unseen data, produce precision, recall, F1-measure and accuracy result of the model and parameter. …”
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  2. 2
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

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

    Published 2014
    “…The extracted features will then be used as an input parameter to classify the staining pattern of the HEp-2 cell images by using Fuzzy Logic. …”
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    Final Year Project
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  3. 3
    A new model for iris data set classification based on linear support vector machine parameter's optimization

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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  4. 4
    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion

    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

    Published 2009
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  5. 5
    Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review

    Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

    Published 2024
    “…Extracted data encompassed subject count, age range, syncope protocols, ML type, hemodynamic parameters, and performance metrics. …”
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  6. 6
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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  7. 7
    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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  8. 8
    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic

    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

    Published 2014
    “…The extracted features are then used as an input parameter to classify five staining patterns by using fuzzy logic. …”
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    Conference or Workshop Item
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  9. 9
    Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som)

    Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som) by Lau, Leh Teen.

    Published 2007
    “…A set of training input data is used to train SOM. The accuracy of classification performance was acquired. …”
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    Final Year Project Report / IMRAD
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  10. 10
    Scene illumination classification based on histogram quartering of CIE-Y component

    Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

    Published 2014
    “…The result of categorization will be validated using inherent illumination data of scene. Applying the improving algorithm for characterizing histograms (histogram quartering) handed out the advantages of high accuracy. …”
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  11. 11
    The formulation of a transfer learning pipeline for the classification of the wafer defects

    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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  12. 12
    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…Power Asymmetry Ratio (PAR) was used for feature extraction. The data involved 96 subjects, were split into 70:30 ratio for training and testing in ANN modelling. …”
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  13. 13
    An improvement of back propagation algorithm using halley third order optimisation method for classification problems

    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
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  14. 14
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  15. 15
    Analyzing land surface temperature in response to massive urbanization by using single window algorithm in Penang Island / Ainna Naeemah Zainal Abidin

    Analyzing land surface temperature in response to massive urbanization by using single window algorithm in Penang Island / Ainna Naeemah Zainal Abidin by Zainal Abidin, Ainna Naeemah

    Published 2019
    “…Next will be the extraction of Land Surface Temperature (LST) by using Spectral Radiance Model and Single Window Algorithm through the satellite imagery. …”
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  16. 16
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  17. 17
    Rethinking environmental sound classification using convolutional neural networks: optimized parameter tuning of single feature extraction

    Rethinking environmental sound classification using convolutional neural networks: optimized parameter tuning of single feature extraction by Al-Hattab, Yousef Abd, Mohd Zaki, Hasan Firdaus, Shafie, Amir Akramin

    Published 2021
    “…We demonstrate that such a simple network can considerably outperform several conventional and deep learning-based algorithms. Through a carefully and empirically parameters fine-tuning of the data input, we reported a model that is significantly less complex in the architecture yet has recorded a similar accuracy of 95.59% compared to state-of-the-art deep models on UrbanSound8k dataset. …”
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  18. 18
    Development Of Vehicle Tracking And Counting System From Traffic Surveillance Video

    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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  19. 19
    Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning

    Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

    Published 2025
    “…Medium tree, Gaussian Naive Bayes and Ensemble Subspace k Nearest Neighbour algorithms are used for classification performance comparison. …”
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  20. 20
    Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis

    Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis by Ahmad Izzuddin, Tarmizi, Mat Safri, Norlaili, Othman, Mohd Afzan

    Published 2021
    “…In order to validate the performance of proposed algorithms, two datasets were used; the first is the publicly available BCI Competition IV dataset 2a, which was often used as a benchmark in validating motor imagery classification algorithms, and the second is a dataset consists of primary data initially collected to study the difference between motor imagery and mental-task associated motor imagery BCI and was used to test the plausibility of the proposed algorithm in highlighting the differences in terms of cortical rhythms. …”
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