Search Results - (( variable detection method algorithm ) OR ( peer estimation method algorithm ))

Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

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Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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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

“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. The Weighted Least Squares (WLS) method is the most popular technique of SE. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…In the third method, a hybrid algorithm called LSTM-C-EST, which is a combination of Fuzzy-MDL and LSTM-C is proposed. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This improved algorithm, known as the edge-template Contour Delineation (etCD), is based on the fusion of edge detection with corner-template detection and dynamic thresholding to produce enhanced edge map. …”
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Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques by Qayyum, A., Malik, A.S., Shuaibu, A.N., Nasir, N.

“…This rPPG signal could perform better as compared to the standard vital signs estimation methods. The Inter beat interval (IBI) based on maximum peak detection approach has been used for heart rate variability estimation. …”
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Human face detection from color images: preliminary result by Chuan, T. S., Setan, Halim, Majid, Zulkepli

“…Our study utilized YCrCb color space method in the detection of human face from a color image with a pre-determine chrominance and luminance parameters. …”
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Improved robust estimator and clustering procedures for multivariate outliers detection by Sharifah Sakinah, Syed Abd Mutalib

“…One of the methods to detect outliers in multivariate data is by using distance-based methods, which is Mahalanobis distance (MD). …”
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Speed sensorless control for PMSM drives using Extended Kalman Filter by Mat Lazi, Jurifa, Nordin, Mohamad Ikhwan, Talib, Md Hairul Nizam, Ibrahim, Zulkifilie

“…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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Error concealment technique using wavelet neural network for wireless transmitted digital images by Al-Azzawi, Alaa Khamees

“…In the case, where the missing regions of pixels are containing textures, edges, and other image features that are not easily handled by concealment algorithms. It therefore, necessitated to use denoising rather than EC algorithms. …”
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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The simulation study demonstrates that, on the whole, the accuracy of the proposed method is better than the competitor methods. The research also develops two new approaches for outlier and potential outlier detection in unimodal and multimodal distributions. …”
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Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

“…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

“…This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. …”
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Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. …”
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Modeling of cupping suction system based on system identification method by Kavindran, Suresh

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Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin by Aziz Jaafar, Nur Mardziah, Noordin, Noraini

“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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