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  1. 1
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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  2. 2
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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  3. 3
    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques

    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

    Published 2023
    Review
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  4. 4
    Recent Advances in Classification of Brain Tumor from MR Images – State of the Art Review from 2017 to 2021

    Recent Advances in Classification of Brain Tumor from MR Images – State of the Art Review from 2017 to 2021 by Ghazanfar, Latif, Faisal Yousif, Al Anezi, Dayang Nurfatimah, Awang Iskandar, Abul, Bashar, Jaafar, Alghazo

    Published 2022
    “…In addition, the review paper will facilitate researchers who are new to machine learning algorithms for brain tumor recognition to understand the basics of the field and pave the way for them to be able to contribute to this vital field of medical research. …”
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  5. 5
    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer

    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

    Published 2023
    “…This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
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  6. 6
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The neural network learns the rough set’s upper and lower approximations as feature extractors simultaneously with classification. …”
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  7. 7
    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome

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

    Published 2014
    “…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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  8. 8
    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing

    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

    Published 2014
    “…Backpropagation NN is supervised learning methods that analyze data and recognize to solve many problems in the real world by building a model that is trained to perform well in some non-linear problems. …”
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  9. 9
    Text classification using Naive Bayes: An experiment to conference paper

    Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

    Published 2005
    “…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
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    Conference or Workshop Item
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  10. 10
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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  11. 11
    Real-time oil palm fruit bunch ripeness grading system using image processing techniques

    Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

    Published 2013
    “…This research has achieved its stated goal of developing a real time oil palm grading system for automated FFB types and ripeness classification. This system will be useful to the oil palm plantations in Malaysia and the rest of the oil-palm growing world. …”
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  12. 12
    Phylogenetic tree classification system using machine learning algorithm

    Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

    Published 2015
    “…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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    Final Year Project Report / IMRAD
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  13. 13
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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  14. 14
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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  15. 15
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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    Final Year Project
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  16. 16
    Autism Spectrum Disorder Classification Using Deep Learning

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

    Published 2021
    “…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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  17. 17
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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  18. 18
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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  19. 19
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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  20. 20
    Using KNN algorithm for classification of textual documents

    Using KNN algorithm for classification of textual documents by Moldagulova A., Sulaiman R.B.

    Published 2023
    Conference Paper
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