Search Results - (( variable detection method algorithm ) OR ( processes estimation methods algorithm ))
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1
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…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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2
Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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3
Power System State Estimation In Large-Scale Networks
Published 2010“…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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4
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Based on previous researches, most existing segmentation methods focused on a specific environment. Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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5
An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…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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6
Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques
Published 2018“…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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7
Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. …”
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8
Detection and classification of moving objects for an automated surveillance system
Published 2006“…This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. …”
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9
Error concealment technique using wavelet neural network for wireless transmitted digital images
Published 2012“…Next, a multi-directional interpolation (MDI) technique is proposed. The method is used to estimate the lost coefficients in the wavelet-domain. …”
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10
Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…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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11
Detection and classification of moving objects for an automated surveillance system
Published 2006“…This thesis focuses on a method to detect and classify a moving object that pass through the surveillance area boundary. …”
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12
On the earthquake distribution modeling in Sumatra by Cauchy cluster process : comparing log-linear and log-additive intensity models
Published 2023“…The estimation procedure follows the standard two-step estimation technique, where the first step adapts the method for the Generalized Additive Models (GAMs) using penalized iteratively reweighted least squares (PIRLS) algorithm, and the second step employs the second-order composite likelihood. …”
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13
Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi
Published 2022“…However, the identification process of tree species and AGB estimation in tropical forest is quite challenging either by traditional or remote sensing methods due to the structure of forest type. …”
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14
Robust Kernel Density Function Estimation
Published 2010“…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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15
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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16
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…So,this optimization method can help to save time and cost of the process. …”
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17
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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18
Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…Ultimately, the results suggest that the proposed ML method can be utilized effectively to accurately estimate the four pollination stages in plantations, becoming a reliable and accurate tool in automated assisted/artificial pollination decision making systems. …”
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19
New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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20
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…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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