Search Results - (( frames detection path algorithm ) OR ( using vectorization learning algorithm ))

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  1. 1

    False path identification algorithm framework for nonseparable controller-data path circuits by Shaheen, Ateeq U. R., Hussin, Fawnizu Azmadi, Hamid, Nor Hisham

    Published 2016
    “…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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    Conference or Workshop Item
  2. 2

    Development of obstable avoidance system for 3D robot navigation by Er, Kai Sheng

    Published 2024
    “…In conclusion, the developed algorithm enables the robot to detect obstacles that are not on the same plane as the 2D LiDAR and cannot be detected using depth camera data.…”
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    Final Year Project / Dissertation / Thesis
  3. 3

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
    Article
  4. 4

    Intelligent auto tracking in 3D space by image processing by Al-Khateeb, Khalid A. Saeed, Awang, Mat Kamil, Khalifa, Othman Omran

    Published 2009
    “…Hence, the spherical coordinates of the target are defined and updated with every TV frame. The time development of the centroid in successive TV frames represents the real time trajectory of the target path. …”
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    Proceeding Paper
  5. 5

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
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    Article
  6. 6

    Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle by Ramli, Muhammad Faiz, Shamsudin, Syariful Syafiq, Legowo, Ari

    Published 2017
    “…In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles…”
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    Article
  7. 7

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
    Article
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    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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    Thesis
  10. 10

    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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    Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points by Ramli, Muhammad Faiz, Sutjipto, Agus G.E., Sulaeman, Erwin, Ari Legowo, Ari Legowo

    Published 2024
    “…A robust system should be able to not only detect obstacles but the free region for the avoidance path as well. …”
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    Conference or Workshop Item
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