Search Results - time ((extraction method) OR (optimization method)) algorithm
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…This thesis presents a new method to extract the most relevant features of iris biometric images for indexing the database within minimum time and search area. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…With SSA optimization, the Sauvola method combined with SVM reaches an accuracy of 99.58%, surpassing other methods that use image processing and ANN classification. …”
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphso...
Published 2022“…The proposed guaranteed convergence arithmetic optimization algorithm based on efficient modified third order Newton Raphson (GCAOAEmNR) method highlights important contributions to the literature in terms of methodology (explorer-exploiter phases) and objective function design. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The results of the comparison indicated that the MADE method has an excellent level of accuracy and outperforms the iterative method in terms of CPU-execution time.…”
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A New Competitive Binary Grey Wolf Optimizer To Solve The Feature Selection Problem In EMG Signals Classification
Published 2018“…To evaluate the effectiveness of proposed method, CBGWO is compared with binary grey wolf optimization (BGWO1 and BGWO2), binary particle swarm optimization (BPSO), and genetic algorithm (GA). …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Automated threshold detection for object segmentation in colour image
Published 2016“…Most common solution of the task is the uses of threshold strategy based on trial and error method. As the method is not automated, it is time consuming and sometimes a single threshold value does not work for a series of image frames of video data. …”
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Face recognition using PZMI, ANN and Ant colony algorithms / Milad Miri
Published 2018“…Algorithms developed for face recognition are tightly related to the rate of extracted face features. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…That is why, image template matching problem is now considered as an optimization problem. By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction
Published 2025“…Emphasis is placed on the optimization of wavelet parameters alongside extraction of key temporal and amplitude-based features such as time difference, charge difference, pulse height, rise time, and pulse width. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…It was found that machine learning algorithms have significantly reduced the signal processing time by 3.5 to 655 times faster than the conventional LCF method. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment
Published 2011“…From a dimensionality reduction evaluation aspect, the average misclassification error of the proposed method in low-rank feature space is 9.6% and same error rate for three other well-known feature extraction methods is 21.21%. …”
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Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
Published 2023“…Hence, in this paper, we propose a genetic algorithm based method with the inclusion of the 'Don't Care' antecedent (hereafter denoted as DC-GA) to the foundation of the O-EGART-PR-FIS, with the aim of further optimizing the existing fuzzy rules. …”
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