Search Results - (( based optimization based algorithm ) OR ( basic estimation method algorithm ))
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…The proposed HPSO algorithm aims to obtain the least number of computations with low degradation value in estimation accuracy. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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Stereo matching algorithm using census transform and segment tree for depth estimation
Published 2023“…The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Optimization-based method for estimating the transmission rate of COVID-19 during the lockdown in Malaysia
Published 2022“…In this work, the optimization-based method is implemented to investigate the effectiveness of lockdown strategies undertaken to contain the COVID-19 during the first two waves in Malaysia. …”
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation
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 -
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images
Published 2018“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…Our method consists of three basic steps. In the first step, a weights-based modified reweighted fast, consistent, and high break-down point is computed. …”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…As a result,it will first introduce the theories about the feature extraction and the basic principles on how feature points can act as locating resynchronization between watermark insertion and extraction discussed in detail.Subsequently,it will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme.Further detailed watermarking schemes which combine feature regions extraction with counter propagation neural network-based watermarks synapses memorization are then presented.The performance of watermarking schemes based on framework of feature point shows the following advantages:a)Good imperceptibility. …”
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OPTIMIZATION-BASED METHOD FOR ESTIMATING THE TRANSMISSION RATE OF COVID-19 DURING THE LOCKDOWN IN MALAYSIA
Published 2023“…In this work, the optimization-based method is implemented to investigate the effectiveness of lockdown strategies undertaken to contain the COVID-19 during the first two waves in Malaysia. …”
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Implementation of Symmetric Rank-One Methods for Unconstrained Optimization
Published 2010“…We then examine a new scaled memoryless SR1 method based on modied secant equation for solving large-scale unconstrained optimization problems. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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