Search Results - (( quality classification using algorithm ) OR ( data visualization learning algorithm ))

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  1. 1

    Machine learning application for concrete surface defects automatic damage classification by Syahrul Fithry Senin, Khairullah Yusuf, Amer Yusuf, Rohamezan Rohim

    Published 2024
    “…This model is trained using 80% of the image data and tested using another 20% of the image data. …”
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    Article
  2. 2

    Classification and visualization: Twitter sentiment analysis of Malaysia’s private hospitals by Abu Samah, Khyrina Airin Fariza, Nor Azharludin, NurMaisarah, Riza, Lala Septem, Hasrol Jono, Mohd Nor Hajar, Moketar, Nor Aiza

    Published 2023
    “…Term frequency-inverse document frequency is used for text mining, information retrieval techniques, and the Naïve Bayes, a machine learning algorithm for the classification. …”
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  3. 3

    Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen by Song , Cheen

    Published 2023
    “…Understanding this association is crucial given the increasing prevalence of air pollution in many regions, particularly in Malaysia, which is affected by air pollution. This study used a comprehensive methodology to investigate the relationship between air pollution and ACS patient outcomes utilizing machine learning (ML) algorithms, including: 1) Linear Regression, 2) Logistic Regression, 3) Support Vector Machine (SVM), 4) Random Forest (RF), 5) XGBoost, 6) Naïve Bayes (NB), and 7) Stacked Ensemble ML utilizing data from the National Cardiovascular Disease Database (NCVD) Malaysia registry and air quality data from the Department of Environment (DOE) Malaysia. …”
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    Thesis
  4. 4

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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    Thesis
  5. 5

    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

    Published 2022
    “…Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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    Thesis
  6. 6

    Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail by ZhongMing, Liao, Ismail, Azlan

    Published 2023
    “…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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  7. 7

    Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

    Published 2015
    “…There is a need to resolve this problem for us to get good water that can be used for domestic purposes. This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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  8. 8

    Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

    Published 2021
    “…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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    Proceeding Paper
  9. 9

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This finding emphasizes that Stacking with Gradient Boosting provides much better performance in water quality classification compared to other models. This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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    Article
  10. 10

    Algorithm visualization design guidelines for mobile leaning by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

    Published 2018
    “…This study is about the algorithm visualization design guidelines for mobile platform, to teach students data structures and algorithm (DSA) subject effectively. …”
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    Article
  11. 11

    Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

    Published 2022
    “…This paper analyzed several visual analytics approaches instantiated in machine learning algorithm for medical record analytics. …”
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    Proceeding Paper
  12. 12

    Designing algorithm visualization on mobile platform: The proposed guidelines by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

    Published 2017
    “…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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  13. 13

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

    Published 2018
    “…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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    Thesis
  14. 14

    Real-time power quality disturbance classification using convolutional neural networks by Husodo, Budi Yanto, Dalimi, Rinaldy, Ihsanto, Eko, Gunawan, Teddy Surya

    Published 2020
    “…Experimental results showed that the proposed algorithm produced a good result with the classification accuracy of 97.52% trained using 100 epochs. …”
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    Book Chapter
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    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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    Article
  17. 17

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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    Thesis
  18. 18

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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    Thesis
  19. 19

    Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mahabob, Noratikah Zawani, Ismail, Nurlaila, Mohd Yusoff, Zakiah, Taib, Mohd Nasir

    Published 2021
    “…So, the output was the classification of quality between low, medium low, medium high or high quality while the input was the abundances (%) of compounds. …”
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    Book Section
  20. 20

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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