Search Results - (( parameter estimation max algorithm ) OR ( frames extraction sensor algorithm ))
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AR oriented pose matching mechanism from motion capture data
Published 2023“…In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). …”
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Improved Location And Positioning Utilizing Single MIMO Base Station In IMT-Advanced System
Published 2016“…This algorithm based on the angle of arrival (AOA) and angle of departure (AOD) measurement parameter completed the new SMBS algorithm with virtual base station (SMVirBS). …”
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3
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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4
HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM
Published 2019“…A video sequence consists of sequences of frame, with the detection algorithm, these frames can be analyzed and detect any” “abnormal behavior such as crime.” …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…This study presents a hybrid approach combining the CatBoost algorithm with metaheuristic optimization techniques to enhance SoC estimation accuracy and robustness. …”
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…In this subsystem, image-capturing techniques capture the video images frame by frame. After that, lane detection process extracts the information about vehicle position with respect to the highway lane. …”
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7
Vision-based autonomous vehicle driving control system
Published 2005“…In this subsystem, image-capturing techniques capture the video images frame by frame. After that, lane detection process extracts the information about vehicle position with respect to the highway lane. …”
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8
Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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9
Slam-based mapping for object recognition
Published 2018“…The SIFT (Scale-Invariant Feature Transform) is used to extract features from the current frame and match with the object database to identify and recognize the object whenever the robot come across the object. …”
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10
New correlation for oil formation volume factor
Published 2014“…It is a family of inductive algorithms which executes computer-based mathematical modeling of multi-parametric data sets. …”
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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow
Published 2025“…Techniques such as Region of Interest (ROI) cropping and multi-section frame extraction were implemented to reduce computational complexity while further enhancing accuracy. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…The first step, ANN was calibrated and validated by using daily observed evapotranspiration, rainfall, and stream flow (2003-2012). In order to estimate daily evapotranspiration, daily observed Min and Max temperature was used in the estimation based on Hargreaves-Samani equation. …”
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14
Analysis of performance between kinect v1 and kinect v2 for various facial part movements
Published 2019“…A total number of 18 desired facial feature point at similar landmarks will be extracted in the format of 3D coordinates for both Kinect cameras. …”
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15
Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
Published 2016“…In this study, the images has been captured using a kinect sensor based skeletal algorithms. The feature extraction was done by normalizing the position and size of the user, by taking eight out of 20 joints that contribute in identifying the movement of the hands; left hand, right hand, left wrist, right wrist, left elbow, right elbow, torso and head. …”
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Analysis of performance between kinetic v1 and Kinect v2 for various facial part movements
Published 2019“…A total number of 18 desired facial feature point at similar landmarks will be extracted in the format of 3D coordinates for both Kinect cameras. …”
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