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  1. 1
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

    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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  2. 2
    An adaptive block-based matching algorithm for crowd motion sequences

    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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  3. 3
    An adaptive block-based matching algorithm for crowd motion sequences

    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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  4. 4
    An Adaptive Motion Estimation Algorithm for Irregular Motion of Objects

    An Adaptive Motion Estimation Algorithm for Irregular Motion of Objects by Kajo, Ibrahim, Malik, Aamir Saeed, Kamel , Nidal

    Published 2014
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  5. 5
    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS

    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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  6. 6
    An adaptive motion estimation algorithm for irregular motion of objects

    An adaptive motion estimation algorithm for irregular motion of objects by Kajo, I., Malik, A.S., Kamel, N.

    Published 2014
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  7. 7
    Multilevel optimization for dense motion estimation

    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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  8. 8
    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE)

    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE) by Saiful Anuar, Abu Bakar, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba

    Published 2012
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  9. 9
    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter

    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

    Published 2019
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  10. 10
    Improved random forest for feature selection in writer identification

    Improved random forest for feature selection in writer identification by Sukor, Nooraziera Akmal

    Published 2015
    “…Writer Identification (WI) is a process to determine the writer of a given handwriting sample. …”
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  11. 11
    Investigation of block matching algorithm for video coding

    Investigation of block matching algorithm for video coding by Faizul Hadi Mohamad Jamil

    Published 2013
    “…The temporal model deals with motion estimation (ME) and motion compensation (MC) algorithm with the matching technique called “Block Matching Algorithm” (BMA) to produce the next encoded video frame with motion vector. …”
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  12. 12
    A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis

    A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis by Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…However in this chapter, feature selection is used to obtain the unique individual significant features which are proven very important in handwriting analysis of Writer Identification domain. …”
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  13. 13
    A new swarm-based framework for handwritten authorship identification in forensic document analysis

    A new swarm-based framework for handwritten authorship identification in forensic document analysis by Pratama, Satrya Fajri, Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…The use of feature selection as one of the important machine learning task is often disregarded in Writer Identification domain, with only a handful of studies implemented feature selection phase. …”
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  14. 14
    Estimation of geometric fractional Brownian motion perturbed by stochastic volatility model

    Estimation of geometric fractional Brownian motion perturbed by stochastic volatility model by Alhagyan, Mohammed, Misiran, Masnita, Omar, Zurni

    Published 2015
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  15. 15
    The impact of executive function and aerobic exercise recognition in obese children under deep learning

    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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  16. 16
    Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model

    Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model by Yazid, Edwar, Liew, M. S., Parman, Setyamartana, Kurian, V.J.

    Published 2013
    “…KEY WORDS: Motion responses; Kalman smoother; Time-varying ARX model; Transfer function.…”
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  17. 17
    Discretization of integrated moment invariants for writer identification

    Discretization of integrated moment invariants for writer identification by Draman @ Muda, Azah Kamilah, Shamsuddin, Siti Maryam, Darus, Maslina

    Published 2008
    “…Hence, in this study, an integrated scaling formulation of Aspect Scaling Invariant is presented in Writer Identification to hunt for the individuality perseverance. …”
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  18. 18
    MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION

    MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

    Published 2016
    “…The Particle Filtering (PF) algorithm is the most extensively used tor generative model based articulated human motion tracking. …”
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  19. 19
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
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  20. 20
    A novel approach to human motion estimation with applications in human-robot safety

    A novel approach to human motion estimation with applications in human-robot safety by Motlagh, O., Tang, Sai Hong, Ismail, Napsiah, Ramli, Abdul Rahman, Samin, Razali

    Published 2008
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