Search Results - (( motion estimation model algorithm ) OR ( label classification using algorithm ))*

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  1. 1

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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    Thesis
  2. 2

    Comparative analysis of text classification algorithms for automated labelling of quranic verses by Adeleke, Abdullah, Samsudin, Noor Azah, Mustapha, Aida, Mohd Nawi, Nazri

    Published 2017
    “…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. …”
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    Article
  3. 3

    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
  4. 4

    An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

    Published 2018
    “…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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    Article
  5. 5

    An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

    Published 2018
    “…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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    Article
  6. 6

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

    Published 2017
    “…As the result, the pattern classification accuracy is also xii increase. For examples, after applying the proposed integration system, the classification accuracy of Fisher’s Iris, Wine and Bacteria18Class has been increased from 88.67% to 96.00%, from 78.33% to 83.45% and from 93.33% to 94.67% respectively as compared to only used unsupervised clustering algorithm. …”
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    Thesis
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    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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    Article
  10. 10

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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    Article
  11. 11

    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…Three steps of improvements had been made to increase the modeling capacity of input-output models. The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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    Thesis
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    Multi label ranking based on positive pairwise correlations among labels by Alazaidah, Raed, Ahmad, Farzana Kabir, Mohsin, Mohamad

    Published 2020
    “…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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    Article
  14. 14

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…Experimental results on three image sequences using four models of optical flow with different computational efforts show that the FMG/Opt algorithm outperforms significantly both the TN and MR/Opt algorithms in terms of the computational work and the quality of the optical flow estimation.…”
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    Monograph
  15. 15

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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    Article
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    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
  20. 20

    Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie by Mat Saffie, Nur Amira

    Published 2019
    “…Furthermore, most classification algorithms, using either fuzzy or non-fuzzy approaches, produce results in the form of crisp or categorical classification outcomes. …”
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    Thesis