Search Results - (( using vector path algorithm ) OR ( data classification learning algorithm ))

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  1. 1

    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

    Published 2023
    “…Besides this, many satellite imagery platforms provide free accessibility of such data. In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
    text::Thesis
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    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

    Published 2015
    “…This research explores path integration in mobile robot navigation and path optimization technique using vector calculus. …”
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    Article
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    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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    Thesis
  6. 6

    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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    Thesis
  7. 7

    Performance of Ad-Hoc on-Demand Distance Vector Discovery Algorithms Based On Packet Lifetime by Ahmad, Noor Azlan

    Published 2008
    “…AODV uses a distance or hop count for determining the best forwarding path and store the sequence number at table entry to ensure the path information is up-to-date. …”
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    Thesis
  8. 8

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

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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    Thesis
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…Feature selection and classification are widely utilized for data analysis. …”
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    Thesis
  11. 11

    Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak by Abdul Razak, Noorfadzli

    Published 2018
    “…The second stage focuses on using the vector to generate an admissible cubic path via Hermite interpolation technique integrated with time and tangent transformation scheme. …”
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    Thesis
  12. 12

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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    Thesis
  13. 13

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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    Thesis
  14. 14

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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    Conference or Workshop Item
  15. 15

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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    Final Year Project / Dissertation / Thesis
  16. 16

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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    Conference or Workshop Item
  17. 17

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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    Article
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    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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    Thesis
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    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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    Conference or Workshop Item
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    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”
    Conference Paper