Search Results - (( parameter simulation model algorithm ) OR ( frames detection sensor algorithm ))
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1
Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…Once the GUI application for simulation is launched, user can enter input parameters value (number of frames, canny edge detection value, vehicle speed, and braking time) in text control to simulate and analyse video images and vehicle driving control. …”
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2
Vision-based autonomous vehicle driving control system
Published 2005“…Once the GUI application for simulation is launched, user can enter input parameters value (number of frames, canny edge detection value, vehicle speed, and braking time) in text control to simulate and analyse video images and vehicle driving control. …”
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3
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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Final Year Project -
4
A monocular view-invariant fall detection system for the elderly in assisted home environments
Published 2011“…An ensemble of pose models performs inference on each video frame. Each pose model employs an expectation-maximization algorithm to estimate the probability that the given frame contains the corresponding pose. …”
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Proceeding Paper -
5
Web Camera Application For Motion Detection
Published 2003“…There are many different ways to detect motion. The conventional way is by using either active sensor or passive sensor. …”
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6
Zero acceleration algorithm with state of motion identifier for position estimation of wheeled robot
Published 2019“…The proposed framework consists of zero acceleration algorithm which responsible to detect the time and duration of a wheeled robot when it is travelling at constant speed (zero acceleration), zero velocity update to detect the still phase of the wheeled robot and improved drift correction. …”
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7
Development of obstable avoidance system for 3D robot navigation
Published 2024“…To prepare for obstacle avoidance algorithm development, a differential drive robot was constructed, and a URDF description was prepared to ensure correct odometry data conversion from sensor coordinate frames to the robot coordinate frame. …”
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Final Year Project / Dissertation / Thesis -
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Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
Published 2017“…In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. …”
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Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
Published 2024“…: This research paper is about method of detection of free region and obstacle region by combining image segmentation and frame subtraction method. …”
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Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway
Published 2023“…Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. …”
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Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion
Published 2021“…The algorithm used for feature detection and description is Oriented-FAST Rotated-BRIEF (ORB), whereas to evaluate the homography for pose estimation, Random Sample Consensus (RANSAC) is used. …”
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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13
Estimation in spot welding parameters using genetic algorithm
Published 2007“…The application has widespread in many areas especially in system and control engineering. Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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14
Around view monitoring system with motion estimation in ADAS application
Published 2019“…The algorithm to be tested is Gunnar Farneback. Movement in sequential frames is detected and converted to the real-world position change. …”
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Proceeding Paper -
15
Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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17
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data
Published 2013“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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Thesis -
20
Passive client-centric rogue access point detection framework for WiFi hotspots
Published 2018“…The proliferation of Wi-Fi hotspots in public places provides seamless Internet connectivity anywhere at any time to the wireless clients.Although many hotspots are often unprotected,unmanaged and unencrypted,this does not prevent the clients from actively connecting to the network.The underlying problem is that the network Access Point (AP) is always trusted.The adversary can impersonate a legitimate AP by setting up a rogue AP to commit espionage and to launch evil-twin attack,session hijacking,and eavesdropping.To aggravate the threats, existing detection solutions are ill-equipped to safeguard the client against rogue AP.Infrastructure- centric solutions are heavily relied on the deployment of sensors or centralized server for rogue AP detection, which are limited,expensive and rarely to be implemented in hotspots.Even though client-centric solutions offer threat-aware protection for the client,but the dependency of the existing solutions on the spoofable contextual network information and the necessity to be associated with the network makes those solutions are not viable for the hotspot’s client.Hence,this work proposes a framework of passive client-centric rogue AP detection for hotspots.Unlike existing solutions,the key idea is to piggyback AP-specific and network-specific information in IEEE 802.11 beacon frame that enables the client to perform the detection without authentication and association to any AP.Based on the spatial fingerprints included in the broadcasted information from the APs in the vicinity of the client,this work discloses a novel concept that enables the rogue AP detection via the client’s ability to self-colocalize and self-validate its own position in the hotspot.The legitimacy of the APs in the hotspot,in this view,lies in the fact that the correct matching between the Received Signal Strength Indicator (RSSI) measurements at the client and pre-recorded fingerprints is attainable when the beacons are transmitted only from the legitimate APs.Hence,any anomalousness in AP’s beacon frame or any attempt to replay the legitimate AP’s beacon frame from different location can be detected and classified as rogue AP threats.Through experiments in real environment,the results demonstrate that with proper algorithm selection and parameters tuning,the rogue AP detection framework can achieve over 90% detection accuracy in classifying the absence and presence of rogue AP threats in the hotspot.…”
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