Search Results - (( course evaluation tree algorithm ) OR ( shape identification clustering algorithm ))

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  1. 1

    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Putra, Azma

    Published 2019
    “…The AR algorithm characterizes the shape of the stress wave signals by AR coefficients and clustered using ‘centroid’ linkages. …”
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    Article
  2. 2

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. …”
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    Thesis
  3. 3

    Dense-cluster based voting approach for license plate identification by Asadzadehkaljahi, Maryam, Shivakumara, Palaiahnakote, Roy, Sangheeta, Olatunde, Mojeed Salmon, Anisi, Mohammad Hossein, Lu, Tong, Pal, Umapada

    Published 2018
    “…This process gives four clusters for the input image. The number of pixels in clusters (dense cluster) and the standard deviation are computed for deriving new hypotheses. …”
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    Article
  4. 4

    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

    Published 2021
    “…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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    Thesis
  5. 5

    Text independent speaker identification using gaussian mixture model by Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain, Tan, Tian Swee, Ariff, Ahmad Kamarul

    Published 2007
    “…For speaker model training, a fast re-estimation algorithm based on highest likelihood mixture clustering is introduced. …”
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    Conference or Workshop Item
  6. 6

    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation by Ismael, Ahmed Naser

    Published 2016
    “…The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold and the use of Euclidean Distance as distance measure. …”
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    Thesis
  7. 7

    Product Identification Using Image Processing And Radial Basis Function Neural Networks by Khairul Azha , A. Aziz, Abdul, Kadir, Rostam Affendi, Hamzah, Amat Amir , Basari

    Published 2015
    “…This paper presents a product identification using image processing and radial basis function neural networks. …”
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    Article
  8. 8
  9. 9

    An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…We developed a set of prediction models with distinct machine learning algorithms. Decision tree triumph over other models and thus is further transformed into easily explicable format. …”
    Article
  10. 10

    Content-based indexing of low resolution documents by Md Nor, Danial

    Published 2016
    “…The proposed identification and indexing method in the thesis uses a Visual Signature (VS). …”
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    Thesis
  11. 11

    Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

    Published 2020
    “…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. This study applies image processing techniques to detect the color and shape of watermelon’s skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon images are used to test the functionality of the proposed detection system in this study. …”
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    Proceeding Paper
  12. 12

    A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…Educational Data Mining tools, specifically Machine learning classifiers, appear supportive to develop prediction models which forecast students� final outcome in a course. This research evaluates the effectiveness of machine learning classifiers to monitor students� academic progress and informs the instructor about the students at the risk of producing unsatisfactory final result in a course. …”
    Conference Paper
  13. 13

    An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

    Published 2024
    “…According to the research, 52% of students who sign up for a course would never read the course materials. Furthermore, throughout the course of five years, the dropout rate reached a stunning 96%. …”
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    Article
  14. 14

    Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

    Published 2024
    “…Particularly, the decision tree is identified as the most accurate predictive model, having a 0.60 accuracy value. …”
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    Thesis
  15. 15

    DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi by Azmi, Muhammad Haziq

    Published 2025
    “…The project will implement automated detection and disease management recommendation algorithms while evaluating the functionality and usability of the designed application. …”
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    Thesis
  16. 16

    Leveraging data lake architecture for predicting academic student performance by Abdul Rahim, Shameen Aina, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, Nurlankyzy, Appak Yessirkep

    Published 2024
    “…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
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    Article