Search Results - (( motion detection ((a algorithm) OR (new algorithm)) ) OR ( swarm optimization max algorithm ))*
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1
A particle swarm optimization and min-max-based workflow scheduling algorithm with QoS satisfaction for service-oriented grids
Published 2017“…It also outperforms the comparison algorithm, with about 30% increase, in terms of cumulative QoS satisfaction of optimization requirements. …”
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2
Performance comparison of differential evolution and particle swarm optimization in constrained optimization
Published 2012“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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3
Web Camera Application For Motion Detection
Published 2003“…The new method to detect motion is "vision motion detection". …”
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4
A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method
Published 2018“…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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5
An evaluation of optical flow algorithms for crowd analytics in surveillance system
Published 2017“…This paper presents an overview of the optical flow methods that used mainly for pedestrian and crowd motion detection. The work focuses on the conventional optical flow method such as Lucas & Kanade and Horn & Schunck methods as well as the most recent methods such as Classic+NL that combines the classic formulation with a new non-local term. …”
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6
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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7
Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Conference or Workshop Item -
8
Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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Video surveillance: explosion detection
Published 2025“…By leveraging three motion-based variables, including motion ratio, new pixel ratio and optical flow values, together with three detection approaches, namely global detection, non-eroded detection and eroded detection, the system demonstrates the effectiveness of motion based methods in detecting explosions at an early stage with acceptable performance. …”
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Final Year Project / Dissertation / Thesis -
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Around view monitoring system with motion estimation in ADAS application
Published 2019“…Here, proposed an AVM system that will integrate with the motion estimation algorithm to produce a good result. …”
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Proceeding Paper -
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation
Published 2000“…Then, various optimized algorithms for the two core processes in the compression, DCT and motion estimation, were reviewed and analyzed. …”
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14
Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…The first contribution of this thesis introduces a robust visual tracking algorithm that is able to locate moving objects in surveillance videos. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…Therefore, a new reference-free damage detection algorithm is proposed. …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem
Published 2010“…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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Improved abnormal detection using self-adaptive social force model for visual surveillance
Published 2017“…The abnormal detection in a crowd is a noteworthy research topic in automated surveillance system in public places. …”
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Reactive memory model for ant colony optimization and its application to TSP
Published 2014“…Ant colony optimization is one of the most successful examples of swarm intelligent systems. …”
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Conference or Workshop Item -
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Article -
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Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal
Published 2025“…This research performs a comparative analysis of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as methods for optimizing the training of ANNs, utilizing three medical datasets: Breast Cancer Wisconsin, Cleveland Heart Disease, and Pima Indian Diabetes. …”
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Thesis