Search Results - (( _ evaluation case algorithm ) OR ( level classification system algorithm ))

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  1. 1

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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    Thesis
  2. 2

    Classification and visualization of e-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi by Ahmad Kushairi, Nuwairah Aimi

    Published 2023
    “…The SVM classifier model successfully classified the reviews with an accuracy of 96.8% during the testing stage of the classification. Aside from that, the system was thoroughly evaluated for its functionality, which passed all test cases with expected performance. …”
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    Thesis
  3. 3

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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    Thesis
  4. 4

    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

    Published 2020
    “…Firstly, intra-severity classification intended to identify the level of severity of the dysarthric speakers. …”
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    Thesis
  5. 5

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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    Academic Exercise
  6. 6

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The developed algorithm was used for the real time specific weed discrimination employing multi-level wavelet decomposition. …”
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    Citation Index Journal
  7. 7

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The developed algorithm was used for the real time specific weed discrimination employing multi-level wavelet decomposition. …”
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    Citation Index Journal
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    Neural network diagnostic system for dengue patients risk classification by Faisal, T., Taib, M.N., Ibrahim, Fatimah

    Published 2012
    “…However, it has been a great challenge for the physicians to identify the level of risk in dengue patients due to overlapping of the medical classification criteria. …”
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    Article
  11. 11

    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…For this purpose, an algorithm which hybridized the Intensity Based Analysis (IBA), Grey Level Co-occurrence Matrices (GLCM), Adaptive Network-based Fuzzy Inference System (ANFIS) and £article ~warm Optimization (PSO) Clustering Algorithm (CAPSOCA) is proposed. …”
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    Thesis
  12. 12

    A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform by Mahmmod, Basheera M.

    Published 2018
    “…In white noise, for example, the average absolute improvements and their corresponding percentage values of the system performance in terms of PESQ, OVL, STOI, and FWSNR in (dB) for the five SNR levels are 0.37 (17.3%), 0.37 (24.7%), 0.59 (7.8%), and 0.06 (7.7%), respectively. …”
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    Thesis
  13. 13

    Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

    Published 2014
    “…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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    Conference or Workshop Item
  14. 14

    Performance evaluation of direction of arrival (DOA) for linear array antenna design using multiple signal classification (MUSIC) algorithm in variation of displacement vectors and... by Hamzah, Norhayati

    Published 2007
    “…In simple terms, these array antennas can reduce the co channel interference and effectively utilize the bandwidth by steering a high gain in the direction of interest and low gains in the undesired directions. In Smart Antenna system, the intelligence of the system depends on the information collected, processed and implemented through an algorithm i.e. …”
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    Thesis
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    File integrity monitor scheduling based on file security level classification by Abdullah, Zul Hilmi, Udzir, Nur Izura, Mahmod, Ramlan, Samsudin, Khairulmizam

    Published 2011
    “…Integrity of operating system components must be carefully handled in order to optimize the system security. …”
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    Conference or Workshop Item
  18. 18

    Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

    Published 2014
    “…This developed method finally will result in a high accuracy and straightforward classification system especially for illumination concept. …”
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    Thesis
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    Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review by Abdul Bujang S.D., Selamat A., Krejcar O., Mohamed F., Cheng L.K., Chiu P.C., Fujita H.

    Published 2024
    “…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
    Review