Search Results - (( framework segmentation means algorithm ) OR ( java data detection algorithm ))
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1
Blood cell image segmentation using unsupervised clustering techniques
Published 2009“…We use blood cell images infected with malaria parasites as cell images for our framework. Methods that involved in this comparison framework are Fuzzy C Means, K Means and Means Shift Analysis. …”
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2
Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring
Published 2016“…The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. …”
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3
An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…This paper demonstrates Particle Swarm Optimization (PSO)- incorporated AlexNet framework for the skin segmentation task. The results from testing the trained model are promising. …”
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4
Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…Most of the existing algorithms consider the noise filtering step precedes trajectory segmentation step which mean that there is no preprocessing method to partition trajectory into set of segments and remove noise points in real time with low computational cost. …”
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5
Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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6
Embedded car plate image recognition system
Published 2008“…Usually, a general framework is: Pre-processing, Bounding, Character Segmentation, and Character Recognition. …”
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7
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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8
Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
Published 2007“…In this research, a novel image segmentation framework, dedicated to region queries in CBIR, is presented. …”
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9
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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10
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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11
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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12
A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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13
A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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14
A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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15
Computed tomography and echocardiography image fusion technique for cardiac images
Published 2016“…It means fusion results in enhanced image quality consequently leads to effective ventricles segmentation. …”
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16
A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…This study proposes a new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping (MVMO-SH) optimisation for planning Photovoltaic Distributed Generation (PVDG) in the urban Radial Distribution Network (RDN). …”
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17
Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…To achieve this aim, this study proposed a novel framework which extracts the mobile device intrinsic fingerprints from near-silent segments by using two spectral analysis approaches: (a) for linearized modeling, the proposed framework uses the cepstrum estimation technique and extracts entropy of Mel-frequency cepstral coefficients (MFCCs), (b) for non-linear modeling, the framework employs higher-order spectral analysis (HOSA) and utilizes the Zernike moments (ZMs) of the bicoherence magnitude and phase spectrum. …”
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18
A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset
Published 2014“…The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.…”
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19
Optimizing E-commerce inventory management using a machine-learning approach
Published 2025“…In addition, clustering algorithms, including DBSCAN and K-means, were applied to segment customers based on purchasing behaviour, with DBSCAN achieving a Silhouette Score of 0.9708, suggesting well-separated clusters. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…Expert feedback validated the framework’s alignment with the Howard-Sheth consumer behavior model and suggested improvements, such as including additional behavior related factors and refining segment categories. …”
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