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1
Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…To deal with these issues, adaptive sampling algorithm is applied to the data points to adhere to the manipulators speed constraints. …”
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2
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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3
An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization
Published 2019“…The objective of this work is to improve our previous action key frames extraction algorithm (AKF) by adapting a threshold which selects action key frames as final key frames. …”
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4
Moving objects detection from UAV captured videos using trajectories of matched regional adjacency graphs
Published 2017“…Specifically, the objectives of this thesis are (i) to develop an image registration technique based on multigraph matching, (ii) to detect occluded objects through exploration of candidate object correspondences in longer frame sequences, and (iii) to develop a robust graph coloring algorithm for multiple moving object detection under different transformations. …”
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5
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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6
Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
Published 2024“…: 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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A study of frame timing synchronization for WiMAX applications
Published 2007“…The two synchronization algorithms analyzed are Schmidl and Cox technique and double sliding window packet detection. …”
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8
A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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9
Single Frame Profilometry With Rapid Phase Demodulation On Colour-Coded Fringes
Published 2019“…Three experiments were carried out to: (i) verify the applicability of the algorithms used in the proposed single-frame profilometry system; (ii) verify the applicability of the proposed phase error compensation algorithm; and (iii) compare the result of the proposed profilometry against the Mitutoyo CRYSTA-Plus M Series 196 coordinate-measuring machine (CMM). …”
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10
Data clustering using the bees algorithm
Published 2007“…K-means clustering involves search and optimization. …”
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11
A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC
Published 2020“…It may mean the detection of an object within a frame and classify it (human, animal, vehicle, building, etc) by the use of some algorithms. …”
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12
An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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13
2D and 3D video scene text classification
Published 2014“…In this paper, we propose a novel horizontal and vertical symmetry feature by calculating the gradient direction and the gradient magnitude of each text candidate, which results in Potential Text Candidates (PTCs) after applying the k-means clustering algorithm on the gradient image of each input frame to verify PTC , we explore temporal information of video by proposing an iterative process that continuously verifies the PTCs of the first frame and the successive frames, until the process meets the converging criterion. …”
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14
Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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15
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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Efficient NASNetMobile-enhanced Vision Transformer for weakly supervised video anomaly detection
Published 2026“…Current video anomaly detection (VAD) methods struggle to prioritize informative frames and lack effective mechanisms to collect both local and global video contexts. …”
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17
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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18
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. …”
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19
Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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20
Discovering optimal clusters using firefly algorithm
Published 2016“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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