Search Results - (( problem segmentation using algorithm ) OR ( code classification using algorithm ))
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES
Published 2022“…The unsupervised segmentation of color-texture regions using J-value segmentation (JSEG) algorithm is one of the most popular and robust unsupervised segmentation algorithms. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…These algorithms have been applied to the problem of image segmentation. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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Source code classification using latent semantic indexing with structural and frequency term weighting
Published 2012“…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images
Published 2010“…Hence involving problem specific information and expert knowledge in designing segmentation algorithms seems to be useful. …”
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Enhanced Clustering Algorithms For Gray-Scale Image Segmentation
Published 2012“…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
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Chain coding and pre processing stages of handwritten character image file
Published 2010“…This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. …”
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Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…A new approach of CS and WDO algorithm is used for selection of optimal threshold value. …”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The developed patterns are applied in the field of real-time analysis. Finally, the algorithm found, which would solve the image segmentation problem.…”
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Scene classification for aerial images based on CNN using sparse coding technique
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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
Published 2023“…The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. …”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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