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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
    “…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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  2. 2
    Emotion Detection Based on EEG Signal

    Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

    Published 2021
    “…Lately, emotion detection through EEG signals had pulled in numerous researchers and numerous algorithm were discovered. Various kinds of features extraction were investigated and different types of classification method were explored. …”
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    Final Year Project
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  3. 3
    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
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  4. 4
    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
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  5. 5
    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
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  6. 6
    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
    “…Therefore, the proposed methods were effective in improving the process of automatic gender recognition from the emotional-based EEG signals.…”
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  7. 7
    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
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  8. 8
    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
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  9. 9
    Multilanguage speech-based gender classification using time-frequency features and SVM classifier

    Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

    Published 2021
    “…In this paper, we propose a time-frequency method for the classification of gender-based on the speech signal. …”
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  10. 10
    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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  11. 11
    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
    “…The trained network is then applied to benchmark classification problems. Based on the experimental results, the optimized DA algorithm is a much better training algorithm for ANNs as compared to the usual gradient-descent backpropagation algorithm since the resultant ANNs trained by the optimized DA achieve higher accuracy. …”
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  12. 12
    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
    “…The final results show that the multiple classifiers have significantly improved the performance of the single classifier. Our method, namely FIS-PNN, successfully predicts PPI with 96% of accuracy, a level that is significantly greater than all other sequence-based prediction methods.…”
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  13. 13
    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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  14. 14
    Filter-Wrapper Methods For Gene Selection In Cancer Classification

    Filter-Wrapper Methods For Gene Selection In Cancer Classification by Alomari, Osama Ahmad Suleiman

    Published 2018
    “…This study proposes new hybrid filter-wrapper methods based on Maximum Relevancy Minimum Redundancy (MRMR) as a filter approach and adapted bat-inspired algorithm (BA) as a wrapper approach. …”
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  15. 15
    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation

    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation by Abayomi, Olalere Olusegun, Ruth, Alara Oluwaseun, Bala, Mohamed Saad, Twibi, Mohamed Farag

    Published 2016
    “…A non-differentiable interactive multi-objective bundle-based optimization method was used in solving this problem. …”
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  16. 16
    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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  17. 17
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. …”
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  18. 18
    Vision based entomology: a survey

    Vision based entomology: a survey by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). …”
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  19. 19
    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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  20. 20
    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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