Search Results - (( motion estimation method algorithm ) OR ( model validation method algorithm ))

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  1. 1
    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar

    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

    Published 2016
    “…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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  2. 2
    Parameter estimation of stochastic differential equation

    Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

    Published 2012
    “…Non-parametric modeling is a method which relies heavily on data and motivated by the smoothness properties in estimating a function which involves spline and non-spline approaches. …”
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  3. 3
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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  4. 4
    Improved abnormal detection using self-adaptive social force model for visual surveillance

    Improved abnormal detection using self-adaptive social force model for visual surveillance by Wan Nur Azhani, W. Samsudin

    Published 2017
    “…For both indoor and outdoor scene, the proposed algorithm outperforms the other methods with accuracy 97% and 100%. …”
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  5. 5
    Sigma point-based fastslam: Solution to slam problem

    Sigma point-based fastslam: Solution to slam problem by Zafizal, Z., Saifudin, Razali, Mohd Razali, Daud, Hamzah, Ahmad

    Published 2016
    “…In addition, this algorithm avoids the calculation of the Jacobian for motion model which could be extremely difficult for high order systems. …”
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  6. 6
    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation

    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation by Din, Abdul Sattar

    Published 2013
    “…The performance of the algorithm was validated and compared against that of the EKF through series of simulations using Stage multi-agent simulator. …”
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  7. 7
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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  8. 8
    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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  9. 9
    ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES

    ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES by KAJO, IBRAHIM

    Published 2015
    “…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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  10. 10
    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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  11. 11
    Fast adaptive motion estimation search algorithm for H.264 encoder

    Fast adaptive motion estimation search algorithm for H.264 encoder by Patwary, Md Anwarul Kaium

    Published 2012
    “…Simulation result shows that as compared to previous research, this algorithm achieves up to average 60% reduction in motion estimation time without degrading the video quality.…”
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  12. 12
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

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

    Published 2015
    “…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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  13. 13
    New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique

    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
    “…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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  18. 18
    An evaluation of optical flow algorithms for crowd analytics in surveillance system

    An evaluation of optical flow algorithms for crowd analytics in surveillance system by Kajo, I., Malik, A.S., Kamel, N.

    Published 2017
    “…The improvement in computational efficiency and increasing interest in robust and accurate motion estimation algorithms lead to increase in the use of optical flow in crowd analytic applications. …”
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  19. 19
    Fast adaptive motion estimation for H.264

    Fast adaptive motion estimation for H.264 by Patwary, Md Anwarul Kaium

    Published 2011
    “…Simulation result shows that compared to Full Search (FS), this algorithm achieves up to 60% reduction in motion estimation time without degrading the video quality.…”
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  20. 20
    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
    “…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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