Search Results - (( parameter simulation model algorithm ) OR ( frames detection sensor algorithm ))

Refine Results
  1. 1

    Vision-Based Autonomous Vehicle Driving Control System by Isa, Khalid

    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. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Vision-based autonomous vehicle driving control system by Isa, Khalid

    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. …”
    Get full text
    Get full text
    Thesis
  3. 3

    HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM by LO , TIMOTHY YIN HONG

    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.” …”
    Get full text
    Get full text
    Final Year Project
  4. 4

    A monocular view-invariant fall detection system for the elderly in assisted home environments by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

    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. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  5. 5

    Web Camera Application For Motion Detection by Koay, Su Yeong

    Published 2003
    “…There are many different ways to detect motion. The conventional way is by using either active sensor or passive sensor. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Zero acceleration algorithm with state of motion identifier for position estimation of wheeled robot by Tan, Zhi Zhong

    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. …”
    Get full text
    Thesis
  7. 7

    Development of obstable avoidance system for 3D robot navigation by Er, Kai Sheng

    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. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  8. 8

    Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle by Ramli, Muhammad Faiz, Shamsudin, Syariful Syafiq, Legowo, Ari

    Published 2017
    “…In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV by Abdul Aziz, Muhamad Wafi, Ramli, Muhammad Faiz

    Published 2024
    “…: This research paper is about method of detection of free region and obstacle region by combining image segmentation and frame subtraction method. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10
  11. 11

    Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion by Alam, Mir Suhail, Morshidi, Malik Arman, Gunawan, Teddy Surya, Olanrewaju, Rashidah Funke, Arifin, Fatchul

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    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. …”
    Get full text
    Get full text
    Final Year Project
  13. 13

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    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. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Around view monitoring system with motion estimation in ADAS application by Rasdi, Muhammad Hannan Fathi, Nik Hashim, Nik Nur Wahidah, Hanizam, Syahirah

    Published 2019
    “…The algorithm to be tested is Gunnar Farneback. Movement in sequential frames is detected and converted to the real-world position change. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  15. 15

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

    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).…”
    Get full text
    Thesis
  17. 17

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    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. …”
    Article
  18. 18

    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    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.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by 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). …”
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    Passive client-centric rogue access point detection framework for WiFi hotspots by Ahmad, Nazrul Muhaimin

    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.…”
    Get full text
    Get full text
    Get full text
    Thesis