Search Results - (( data detection method algorithm ) OR ( frames estimation using algorithm ))
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1
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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Article -
2
Image Stitching Of Aerial Footage
Published 2021“…ScaleInvariant Feature Transform (SIFT) approach is used to detect and describe the feature points of the extracted frames. …”
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Final Year Project / Dissertation / Thesis -
3
Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking
Published 2012“…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. The solution consists of an algorithm for automatic collection of candidate seed points using efficient grid line searching mechanism and a validation method which uses local geometric and intensity based features as effective validation rules to discriminate between the actual seed point and false alarms. …”
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4
Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. …”
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5
Detection and classification of moving objects for an automated surveillance system
Published 2006“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. …”
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6
Detection and classification of moving objects for an automated surveillance system
Published 2006“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. …”
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Thesis -
7
Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli
Published 2022“…Recently, the integration of computer vision and machine learning has given solutions to improve the underwater detection system by using intelligent classifier algorithm in real-time computer vision to detect underwater animals with challenging environments. …”
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Thesis -
8
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…In the video and frame selection, pre-defined video which have different type of motion and size is used for the algorithm evaluation purpose. …”
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Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin
Published 2021“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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Article -
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Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud
Published 2008“…Each of the video frames is divided into macroblocks. The computational of the current pixel in current frame is compared to the previous decoded frame as a reference. …”
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Thesis -
12
Adaptive framed pseudo-Bayesian Aloha algorithm with priorities
Published 2000“…A new wireless framed pseudo-bayesian Aloha algorithm with adaptive priorities, for wireless ATM reservation-based TDMA MAC prolocols, is presented. …”
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Article -
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Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering
Published 2023“…In the initialization stage, the reader uses improved K-means clustering running concurrently with a tag counter algorithm to cluster tags into K groups using tags RN16 while the counter returns an accurate tag number estimate. …”
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REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
Published 2011“…The practical application of DVC is referred to as Wyner-Ziv video coding (WZ) where an estimate of the original frame called "side information" is generated using motion compensation at the decoder. …”
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15
Investigation of block matching algorithm for video coding
Published 2013“…The temporal model deals with motion estimation (ME) and motion compensation (MC) algorithm with the matching technique called “Block Matching Algorithm” (BMA) to produce the next encoded video frame with motion vector. …”
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16
Block Motion Estimation Using Directional Adaptive Search Window
Published 2006“…Motion estimation (ME) is the exploitation of similarities between adjacent frames in a video sequences, and is an essential part of the H.264 and other video compression standards. …”
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Conference or Workshop Item -
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Zero acceleration algorithm with state of motion identifier for position estimation of wheeled robot
Published 2019“…Position estimation system using inertial sensor poses a critical challenge to deliver accurate positioning information. …”
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18
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Based on the theoretical and fundamental research analysis the FUHS16 and UHDS16 algorithms using 16 × 16 block-based motion estimation formulations were developed. …”
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Book Chapter -
19
Block motion estimation using directional adaptive search window
Published 2007“…Motion estimation (ME) is the exploitation of similarities between adjacent frames in a video sequences, and is an essential part of the H.264 and other video compression standards. …”
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Conference or Workshop Item -
20
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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