Search Results - (( motion optimization based algorithm ) OR ( using classification using algorithm ))
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Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions
Published 2013“…Between the Levenberg-Marquardt and scaled conjugate gradient learning algorithms, the aforesaid algorithm shows better classification performance. …”
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper -
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EMG motion pattern classification through design and optimization of Neural Network
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Working Paper -
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The use of artificial neural network in the classification of EMG signals
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been employed for the classification of EMG signals. …”
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Proceeding Paper -
5
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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Thesis -
6
Electromyography signal processing based on time and time-frequency representations for prosthesis application
Published 2014“…As a result, the output of the proposed algorithm for EMG signal processing using various techniques presented an improvements in EMG signal classification in terms of accuracy. …”
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7
Hand motion detection from EMG signals by using ANN based classifier for human computer interaction
Published 2011“…In this work, the detection of different hand movements (left, right, up and down) was obtained using artificial neural network (ANN). A back-propagation (BP) network with Levenberg-Marquardt training algorithm was utilized. …”
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Proceeding Paper -
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…The current study of the hand posture classification requires a higher number of EMG sensor used to achieve an accurate classification performance that leads the system to be complicated. …”
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Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…The conjugate gradient (CG) method is widely recognised as one of the most efficient numerical methods for solving unconstrained optimization problems. Various studies have been undertaken by implementing the CG method in image restoration, optimal rocket landing guidance and motion control field. …”
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10
Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model
Published 2020“…In this paper, the detection of arousal events is performed using an automatic analysis of EEG and ECG signals. …”
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Conference or Workshop Item -
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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12
Runtime reduction in optimal multi-query sampling-based motion planning
Published 2023“…Algorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planning…”
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Hierarchical approach for articulated 3D human motion tracking using PF-based PSO
Published 2014“…In vision-based human motion tracking, two algorithms most extensively have been used, namely, PF and PSO. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Book Chapter -
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…The development of the Fuzzy Logic Controller requires information on the PID controller parameters that will be fuzzified and defuzzied based on the resulting 49 fuzzy rules. Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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Article -
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Application of sampling-based motion planning algorithms in autonomous vehicle navigation
Published 2016“…In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. …”
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Book Section -
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The impact of executive function and aerobic exercise recognition in obese children under deep learning
Published 2025“…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
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Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Monograph -
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…The development of the Fuzzy Logic Controller requires information on the PID controller parameters that will be fuzzified and defuzzied based on the resulting 49 fuzzy rules. Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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