Search Results - (( model evaluation from algorithm ) OR ( motion estimation swarm algorithm ))*

A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

“…Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

“…Most recently. the swarm-intelligence based PSO algorithm have been gaining momentum in this tield.…”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

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

“…Unfortunately, many of the most popular approaches for cooperative localization in literature today are probabilistic, which are computationally complex and less tolerant to any deviation from their predetermined probabilistic motion and observation models. This research focuses on devising a computationally simpler non-probabilistic cooperative position tracking algorithm specifically for a large swarm of simple mobile robots with the purpose of reducing the error accumulation in the position estimates of an individual robot due to noise in odometric measurement. …”
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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

“…The aggregation algorithms were employed on the forecasts obtained from all individual NN models as well as on a number of the best forecasts obtained from the best NN models. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”

Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
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Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network by Asrul, Adam, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Marizan, Mubin

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala’s, Acir’s, Liu’s, and Dingle’s peak models. …”
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Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…The study of the multistep ahead forecast is significant for practical application purposes using the proposed statistical model. This study is proposing a new algorithm of Box-Jenkins and GARCH (or BJ-G) in evaluating the multistep forecasting performance of the BJ-G model for highly volatile time series data. …”
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An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

“…Also, for a more efficient exploration of students‟ data collected for this research, a Rule-Based Algorithm is proposed and implemented. The predictive models emanated from the two approaches were evaluated in order to validate their effectiveness. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

“…The proposed algorithm is characterized by a search model namely the sensitive search model, where the exploitation-exploration is adaptively balanced. …”
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Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

“…How far the proposed agent-based model for CPS is able to help novice programmer is evaluated by conducting a group based experiment with 35 students from Faculty of Computer Science and Information Technology (FSKTM). …”
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Performance evaluation of state-of-the-art 2D face recognition algorithms on real and synthetic masked face datasets by Khan, Mohammad Amir, Faizabadi, Ahmed Rimaz, Rashid, Muhammad Mahbubur, Zaki, Hasan Firdous

“…On a larger-scale dataset MLFW, the impact of mask-wearing on FR models was also up to 50%. We trained and evaluated a proposed Mask Face Recognition (MFR) model whose performance is much better than the SOTA algorithms. …”
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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…The knowledge obtained from the rules-based model was evaluated through knowledge analysis conducted by technical and domain experts. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making by Mohamad Daud, Nur Hafiza, Shafii, Nor Hayati, Md Nasir, Diana Sirmayunie, Fauzi, Nur Fatihah

“…Upon evaluating the models, the findings reveal notable differences in accuracy. …”
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