Search Results - (( motion evaluation search algorithm ) OR ( evolution optimization method algorithm ))*
Search alternatives:
- evolution optimization »
- motion evaluation »
- evaluation search »
- method algorithm »
-
1
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…To evaluate the performance of the developed algorithm, the average PSNR value, average search point and average elapsed processing time is calculated. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. …”
Get full text
Get full text
Get full text
Book Chapter -
3
New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…There are 6 main designs that the algorithms proposed namely the Orthogonal-Diamond Search Algorithm with Small Diamond Search Pattern (ODS-SDSP), the Orthogonal-Diamond Search Algorithm with Large Diamond Search Pattern (ODS-LDSP), the Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (DOS-SDSP), the Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (DOS-LDSP), the Modified Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (MDOS-SDSP), and the Modified Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (MDOS-LDSP). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
4
A review on particle swarm optimization algorithm and its variants to human motion tracking
Published 2014“…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. 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. …”
Get full text
Get full text
Article -
5
Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud
Published 2008“…A modified of Cross-Diamond-Hexagonal search (MCDHS) based on the Cross-Diamond-Hexagonal search (CDHS) is proposed to match or increase the performance of the Peak-signal-to-noise ratio (PSNR) and reduce the computational complexity of previous motion estimation techniques such as Three Step search (TSS), Simple and Efficient Three Step search (SESTSS), New Three Step search (NTSS), Four . …”
Get full text
Get full text
Thesis -
6
-
7
Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system
Published 2019“…The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. …”
Get full text
Get full text
Article -
8
-
9
Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
Get full text
Get full text
Thesis -
10
Synchronous gravitational search algorithm vs asynchronous gravitational search algorithm: a statistical analysis
Published 2014“…Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. …”
Get full text
Get full text
Conference or Workshop Item -
11
Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
Get full text
Get full text
Get full text
Monograph -
12
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
Get full text
Get full text
Get full text
Article -
13
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
Get full text
Get full text
Article -
14
Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy
Published 2019“…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
Get full text
Get full text
Conference or Workshop Item -
15
Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
Published 2014“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
Get full text
Get full text
Book -
16
HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD
Published 2016“…This metadology way uses an algorithm which combines Pinch Design Method and Differential Evolution Method. …”
Get full text
Get full text
Thesis -
17
Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method
Published 2016“…The results obtained by using the DE method were compared with those obtained by genetic algorithm (GA) method. …”
Get full text
Get full text
Thesis -
18
Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
19
Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE
Published 2015“…In this chapter, the technical issues of two-stage TEC were discussed. After that, a new method of optimizing the dimension of TECs using differential evolution to maximize the cooling rate and coefficient of performance was proposed. …”
Get full text
Get full text
Book -
20
A holistic review on artificial intelligence techniques for well placement optimization problem
Published 2020“…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
Get full text
Get full text
Article
