Search Results - (( motion extraction method algorithm ) OR ( inspired classification approach algorithm ))
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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Academic leadership bio-inspired classification model using negative selection algorithm
Published 2015“…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…Therefore, we conclude that the proposed BFOA-G is the best algorithm in the study, and PG approach is recommended for further development of BFOA as an IS algorithm.…”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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Fast adaptive motion estimation search algorithm for H.264 encoder
Published 2012“…Motion estimation is a technique of video compression and video processing applications; it extracts motion information from the video sequence. …”
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A survey : particle swarm optimization-based algorithms for grid computing scheduling systems.
Published 2013“…This study surveys PSObased scheduling algorithms for Grid systems and presents a classification for the various approaches adopted. …”
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A new search and extraction technique for motion capture data
Published 2008“…Results from the experiments show that matching motion files were successfully extracted from the motion capture library using the new algorithm based on different human body segments.…”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks
Published 2025“…Key contributions include a comparative analysis of evolutionary, swarm intelligence, physics-based, human-inspired algorithms, and hybrid approaches benchmarked on classification datasets. …”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…The method employs the RADICAL technique to extract independent subcomponents. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Here, three improved learning approaches inspired by artificial honey bee's behavior are used to train MLP. …”
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Filter-Wrapper Methods For Gene Selection In Cancer Classification
Published 2018“…This study proposes new hybrid filter-wrapper methods based on Maximum Relevancy Minimum Redundancy (MRMR) as a filter approach and adapted bat-inspired algorithm (BA) as a wrapper approach. …”
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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…It is designed to incorporate with the CAPSOCA algorithm which intended to strengthen the classification outcomes. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Red blood cells classification with sharpening segmentation and mask R-CNN
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Motion detection using Horn-Schunck optical flow
Published 2012“…This system is design to detect motion in a crowd using one of the optical flow algorithms, Horn-Schunck method. …”
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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A method for motion tracking of ventricular endocardial surface
Published 2014“…The present invention relates to a method for automatic motion tracking of ventricular endocardial surface in three dimensional (3D) echocardiography, characterized by the steps of extracting a plurality of ventricular endocardial contours over a complete cardiac cycle; identifying a plurality of landmarks on each ventricular endocardial contour; measuring displacement vector flow (DVF) for each landmark by comparing a pair of consecutive ventricular endocardial contours; measuring velocity vector flow (VVF) for each landmark from end-diastolic (ED) to end-systolic (ES) and vice versa; identifying at least four landmarks from the plurality of landmarks on each ventricular endocardial contour to represent anatomical landmarks of left lateral surface, right lateral surface, inferior wall and anterior wall by using geometrical distance calculation (GDC) algorithm; analysing ventricular endocardial motion direction using a fuzzy logic analyzer (FLA) for the four landmarks identified; updating values of the displacement vector flow (DVF) and velocity vector flow (VVF) based on the ventricular endocardial motion direction; and generating graphical curves of time versus values of the displacement vector flow (DVF) and velocity vector flow (VVF) for the four landmarks identified.…”
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Hyperparameter Optimization of Evolving Spiking Neural Network for Time-Series Classification
Published 2022“…Spiking neural networks are the third generation of artificial neural networks that are inspired by a new brain-inspired computational model of ANN. …”
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