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1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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2
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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3
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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4
An expanded square pattern technique in swarm of quadcopters for exploration algorithm
Published 2017“…In this algorithm, the expanded square pattern is conducted by a series of distance around a fixed reference point. …”
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5
Performance evaluation of marker recognition algorithm for mobile augmented reality in the real environment
Published 2023“…Hence, a performance evaluation of the AR algorithm in a real controlled environment is proposed in this paper. …”
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6
Comparison of performance and computational complexity of nonlinear active noise control algorithms
Published 2011“…The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. …”
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7
Simulation of fast recursive least square algorithm for echo cancellation system
Published 2003“…The performance of echo canceller depends on the choice of the adaptive filtering using Fast Recursive Least Square (FRLS) algorithm. This thesis described the performance of Fast Recursive Least Square (FRLS) algorithm for transversal filter and recursive filter for echo cancellation system in a typical telephone network. …”
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8
An evaluation of feature selection technique for dendrite cell algorithm
Published 2014“…From the experiment, the Rough Set Genetic Algorithm reduct is found to be the most effect feature selection for dendrite cell algorithm when it generates a consistent result for all evaluation metrics. …”
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9
Square groove detection based on forstner with canny edge operator using laser vision sensor
Published 2023“…The objectives of 1his research are to develop a detection algorithm 1hat can extract 1he feature points of1he square-groove; and 1he second objective is to evaluate 1he detection algorithm and its ability to extract 1he image features of 1he square-groove in temis of 1he accuracy. …”
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10
Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector
Published 2025“…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”
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11
A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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12
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. Motivated by this fact, a quantum calculus-based noisy links incremental least mean squares (NL-qILMS) algorithm is proposed. …”
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13
Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining
Published 2019“…The results of three filter feature selection algorithms are evaluated. The result of the paper extracted that Chi-Square and ReliefF perform better than FCBF on a dataset with larger number of features, however the performance of three selected algorithms is found worst on a student dataset with less number of instances. …”
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14
Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining
Published 2019“…The results of three filter feature selection algorithms are evaluated. The result of the paper extracted that Chi-Square and ReliefF perform better than FCBF on a dataset with larger number of features, however the performance of three selected algorithms is found worst on a student dataset with less number of instances. …”
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15
Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…Method 1 is a modification of Sebert’s method where the list squares (LS) fit is replaced by the least median of squares (LMS) fit while Method 2 is a modification of Sebert’s method where the least squares (LS) fit is replaced by the least trimmed of squares (LTS) fit. …”
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16
Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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17
Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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18
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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20
System identification using Extended Kalman Filter
Published 2017“…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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