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  1. 1
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…People with autism are saddled with communication problems, difficulties in social interaction and displaying repetitive behaviours. Several methods have been used to classify the ASD from non-ASD people. …”
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  2. 2
    Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor

    Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor by Faridatul Akma, Mohd Noor

    Published 2010
    “…The result of this research can be uses for segmentation and classification process. …”
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  3. 3
    Development of interactive application for classification of Artocarpus Species

    Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

    Published 2020
    “…The aim of this research is to identify the classification of Artocarpus species by using interactive application and the effectiveness of the interactive application for classification of Artocarpus species. …”
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    Undergraduate Final Project Report
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  4. 4
    BRAIN ACTIVITIES FOR MOTOR MOVEMENT

    BRAIN ACTIVITIES FOR MOTOR MOVEMENT by ., WAFAA ELSAYED ELBASTY

    Published 2012
    “…Feature vectors are used to differentiate the different brain activity signals associated with the user’s attention, Linear Discriminate Linear (LDA) method is used in feature classification step to achieve these goals. …”
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    Final Year Project
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  5. 5
    Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm

    Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm by Addie Irawan, Hashim, Marni Azira, Markom, Abdul Hamid, Adom, Mohd Muslim Tan, E. S.

    Published 2017
    “…The localisation algorithm is developed using scan matching method which is incorporated with K-nearest neighbours (KNN) classification. …”
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  6. 6
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  7. 7
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  8. 8
    Emotion Detection Based on EEG Signal

    Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

    Published 2021
    “…Wavelet transform scalogram is used as feature extraction method. After that, the signal go through Convolutional Neural Network (CNN) for classification.…”
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  9. 9
    Gender classification based on asian faces using deep learning

    Gender classification based on asian faces using deep learning by Janahiraman T.V., Subramaniam P.

    Published 2023
    Conference Paper
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  10. 10
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    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%). …”
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  11. 11
    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs

    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2021
    “…Moreover, the results show significant enhancement in the overall accuracy of classification achieved by using the BGSA optimization algorithm with the proposed hybrid SEA set when compared to individual features. …”
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  12. 12
    An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification

    An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification by Hussain, A., Hussain, S.S., Uddin, M.M., Zubair, M., Kumar, P., Umair, M.

    Published 2022
    “…In this study, exhaustive empirical research of the machine learning algorithm for hand posture classification has been established. …”
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  13. 13
    EEG EYE STATE IDENTIFICATION BASED ON STATISTICAL FEATURES AND COMMON SPATIAL PATTERN

    EEG EYE STATE IDENTIFICATION BASED ON STATISTICAL FEATURES AND COMMON SPATIAL PATTERN by WANG, CHIA WOON

    Published 2019
    “…Besides, common spatial pattern (CSP) is the well-known method for classification algorithm in the BCI field. …”
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    Final Year Project
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  14. 14
    Intuitive content management system via manipulation and duplication with if-else rules classification

    Intuitive content management system via manipulation and duplication with if-else rules classification by Chan, Chung Hoong

    Published 2018
    “…An ICMS is a content management system that uses three main important techniques to build, such as Manipulation method, Data Mining Prediction, and Boyer-Moore Horspool algorithm. …”
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  15. 15
    FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information

    FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information by Sakhinah Abu Bakar, Javid Taheri, Albert Y Zomaya

    Published 2012
    “…As a result, they must interact with each other. In this study we used our approach, namely FIS-PNN, to predict the interacting proteins in yeast from the information of their secondary structures using hybrid machine learning algorithms. …”
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  16. 16
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
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  17. 17
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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  18. 18
    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms

    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

    Published 2023
    “…The algorithms are Decision Tree (c4.5), Linear Regression (LR), and Decision Forest (DF) with a 10-fold cross-validation method for training and testing. …”
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  19. 19
    A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping

    A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

    Published 2014
    “…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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  20. 20
    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration

    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

    Published 2014
    “…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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