Search Results - (( frames detection sensor algorithm ) OR ( parameter detection method algorithm ))

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

“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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Vision-based autonomous vehicle driving control system by Isa, Khalid

“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM by LO , TIMOTHY YIN HONG

“…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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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

“…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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Web Camera Application For Motion Detection by Koay, Su Yeong

“…There are many different ways to detect motion. The conventional way is by using either active sensor or passive sensor. …”
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Zero acceleration algorithm with state of motion identifier for position estimation of wheeled robot by Tan, Zhi Zhong

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

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

“…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 by Abdul Aziz, Muhamad Wafi, Ramli, Muhammad Faiz

“…: 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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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

“…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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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Around view monitoring system with motion estimation in ADAS application by Rasdi, Muhammad Hannan Fathi, Nik Hashim, Nik Nur Wahidah, Hanizam, Syahirah

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

“…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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Application of weighted average on modal parameters for damage detection algorithms: Case study on steel beam by Fayyadh, M.M., Abdul Razak, H.

“…This study verifies the use of the proposed weighting method by Fayyadh and Abdul Razak (2011a) for damage detection algorithms applied on cracked steel beam. …”
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Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Design and development of single-axis solar tracking system and water level control for application of line focus concentrator for solar desalination process by Muhammad Adam, Zahari

“…It was programmed to detect sunlight via the LDRs before actuating the motor to position the parabolic frame. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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