Search Results - (( variable detection method algorithm ) OR ( variable reduction learning algorithm ))
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Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques
Published 2025“…This study investigates the application of machine learning algorithms for the detection of ischemic stroke using CT brain images. …”
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2
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RSNN provides a novel methodology for designing nonlinear filters without prior knowledge of the problem domain. The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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3
Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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4
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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5
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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6
Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti...
Published 2018“…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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7
Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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8
A real time road marking detection system on large variability road images database
Published 2017“…One of the first embedded system is a lane detection system, which was implemented using road marking detection algorithms with the aim to produce a system that is able to detect various shapes of road markings on the images that are captured under various imaging conditions. …”
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9
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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10
Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…The proposed system consists of a combination of Inverse Perspective Transform method, an image enhancement method and edge detection method. …”
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11
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Monograph -
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Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…Results showed that the developed FDD algorithm successfully detect and diagnosed the pre-designed faults. …”
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13
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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14
Integrated face detection approach for far image application
Published 2016“…The noise reduction method in the proposed algorithm consists of a combination of a morphological filter and a rejection method. …”
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15
Variable step size least mean square optimization for motion artifact reduction: A review
Published 2019“…Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). …”
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16
Image Based Congestion Detection Algorithms And Its Real Time Implementation
Published 2015“…The proposed system uses a fast and reliable method to detect traffic congestions. The methodology includes vehicle detection by using backlight pairing feature algorithm and modified Watershed algorithm. …”
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17
Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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18
Fault detection and diagnosis for gas density monitoring using multivariate statistical process control
Published 2011“…Results show that method based on PCA and PCorrA was able to detect the pre-designed faults successfully and identify variables which cause the faults.…”
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Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach
Published 2020“…This method uses an improved Pan-Tompkins algorithm from the previous work with independent of the isoelectric line approach for detecting the QRS onset and the T offset. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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