Search Results - (( motion evaluation process algorithm ) OR ( criteria classifications using algorithmic ))

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  1. 1

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…In the video and frame selection, pre-defined video which have different type of motion and size is used for the algorithm evaluation purpose. …”
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    Thesis
  2. 2

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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    Book Chapter
  3. 3

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Algorithms are used to find the solutions through the computer program. …”
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    Monograph
  4. 4

    New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique by Hamid, Nurul 'Atiqah

    Published 2016
    “…Evaluation is based on the algorithm performances in terms of the search points needed to find the final motion vector, the Peak-Signal to Noise Ratio (PSNR) of the algorithms, and the runtime performance of algorithm simulations. …”
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    Thesis
  5. 5

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…The use of information gain in the ID3 algorithm as the attribute selection criteria is not to assess the relationship between classification and the dataset’s attributes. …”
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    Article
  6. 6

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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    Article
  7. 7

    Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

    Published 2000
    “…Then, various optimized algorithms for the two core processes in the compression, DCT and motion estimation, were reviewed and analyzed. …”
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    Thesis
  8. 8

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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    Article
  9. 9

    Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
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    Article
  10. 10
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    Winsorize tree algorithm for handling outliers in classification problem by Ch’ng, Chee Keong

    Published 2016
    “…This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
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    Thesis
  12. 12

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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    Conference or Workshop Item
  13. 13

    Image restoration techniques for removal of blurred images / Ameer Naeemi Zyarah by Ameer, Naeemi Zyarah

    Published 2017
    “…Blurring is introduced in the process of imaging due to relative motion between camera and scene, atmospheric turbulence, etc. …”
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    Thesis
  14. 14

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
    “…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
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    Article
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    Driver drowsiness detection using different classification algorithms by Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami

    Published 2020
    “…Hence, this paper present and prove the reliability of ECG signal for drowsiness detection in classifying high accuracy ECG data using different classification algorithms.…”
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    Proceeding Paper
  17. 17

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…From a group of 1480 patients drawn from the Acute Coronary Syndrome Malaysian registry, 302 people satisfied the inclusion criteria, and 54 variables were duly considered. Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
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    Thesis
  18. 18

    Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

    Published 2019
    “…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
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    Conference or Workshop Item
  19. 19

    Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

    Published 2019
    “…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
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    Conference or Workshop Item
  20. 20

    Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

    Published 2010
    “…The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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    Conference or Workshop Item