Search Results - (( motion selection means algorithm ) OR ( panel optimization mead algorithm ))
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility
Published 2018“…Geometric Fractional Brownian Motion (GFBM) model is widely used in financial environments. …”
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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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Detection and classification of moving objects for an automated surveillance system
Published 2006“…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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Parameter estimation of stochastic differential equation
Published 2012“…To overcome the subjective and tedious process of selecting the optimal knot and order of spline, an algorithm was proposed. …”
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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 perforin the entire task from low level detection to higher level motion analysis. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…To improve the proposed algorithm, GA was utilized to identify the best choice for ‘‘mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function. …”
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9
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Although motor imagery signals have been used in assisting the hand grasping motion amongst others motions, nonetheless, such signals are often difficult to be generated. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…The parametric model involves the mapping of the sEMG signals to the knee joint moment. Obviously, selecting four muscles to attain a full joint moment and motion is not sufficient, therefore we introduced the net joint moment obtained from the inverse dynamics to optimize the predicted joint moment. …”
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Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles
Published 2025“…While 3D mapping is foundational for reliable AV navigation, its accuracy is often compromised by poor LiDAR sensor calibration and external factors such as motion distortion. This study investigates the physical calibration of a LiDAR sensor mounted on a moving vehicle and its effect on 3D map generation using the HDL Graph SLAM algorithm. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players
Published 2025“…The optimal model was selected based on the mean area under the receiver operating characteristic curve (AUC-ROC) across 10 cross-validation runs and was used with Shapley Additive exPlanations to analyze the risk factors. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Subsequently,the filtered signal containing useful information was extracted by three methods root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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