Search Results - (( using automatic means algorithm ) OR ( variable detection means algorithm ))
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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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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Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…A completely automated system means a computer will perform the entire task from low level detection to higher level motion analysis. …”
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Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset
Published 2018“…The evaluation on the performance is based on volumetric overlap error (VOE), relative volume difference (RVD) and dice similarity coefficient (DSC). The proposed algorithm provided mean VOE of 26.50%, mean RVD of 15.09% and mean DSC of 0.8421. …”
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Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering
Published 2004“…In this paper we proposed an efficient clustering technique referred to as 'similarity index fuzzy c-means clustering'. This technique uses the conventional fuzzy c-means clustering preceded by a technique based on similarity indexing to automatically cluster input data which are relevant to the system. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The classical correlation estimators that employ the sample mean of the dependent and independent variables are known to be affected by outliers. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Published 2008“…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…In this study, the wavelet transform (WT) de-noising technique, linear spectral mean frequency ( meanF) and nonlinear multiscale fuzzy entropy ( MFE) features were used. …”
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Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring
Published 2016“…The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. …”
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Automatic Textile Stain Detection Using Yolo Algorithm
Published 2024“…This research paper proposes a novel approach for automatic textile stain detection using the YOLO (You Only Look Once) algorithm, a state-of-the-art object detection model. …”
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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
Published 2011“…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
Published 2009“…The objectives of this project are to implement automatic annotation for images using K-means clustering, to develop an automatic image annotation prototype using color segmentation and to test the efficiency of the automatic image annotation prototype. …”
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Enhancement of Space-Time Receiver Structure with Multiuser Detection for Wideband CDMA Communication Systems
Published 2006“…We consider two different pilot symbol assisted adaptive beamforming algorithms, Least Mean Square (LMS) and Recursive Least Square (RLS). …”
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Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map
Published 2023“…This research has 3 objectives To develop algorithms for detecting heart conditions as either abnormal or normal using the modified cognitive map (CM) approach, To develop detection algorithms for anomalous heart conditions based on the enhancement of Certainty Factor (CF) technique, and To evaluate and validate the effectiveness of the new proposed model specifically the Certainty Cognitive Map (CCM) for identifying heart defects. …”
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Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease
Published 2024“…However, the high cost of semantic segmentation has limited the development of TB automatic recognition to some extent. To address this issue, we developed an algorithm that automatically generates a semantic segmentation mask of TB from the TB target detection boundary box. …”
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