Search Results - (( code classifications learning algorithm ) OR ( based segmentation modified algorithm ))
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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Proceeding Paper -
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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. …”
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Variational model with image denoising fitting term for boundary extraction of breast ultrasound images
Published 2023“…Consideration of four distinct image Denoising algorithms—Gaussian filter, Median filter, Wiener filter, and Rudin-OsherFatemi (ROF) algorithm—as the new fitting terms in the CDSS model leads to four variants of modified CDSS models called Modified CDSS based on Gaussian filter (MCDSSG), Modified CDSS based on Median filter (MCDSSM), Modified CDSS based on Wiener filter (MCDSSW) and Modified CDSS based on ROF (MCDSSROF). …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES
Published 2022“…This thesis proposed a modified JSEG algorithm to solve the problem of over segmentation when applying it to underwater coral reef images.…”
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Thesis -
6
An evolutionary harmony search algorithm with dominant point detection for recognition-based segmentation of online Arabic text recognition
Published 2014“…At first, the pre-segmentation algorithm uses a modified dominant point detection algorithm to mark a minimal number of points which defines the text skeleton. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach
Published 2023“…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”
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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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A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239)
Published 2020“…In this research, a region-based active contour, which is regarded as an energy-minimizing process, is used for the purpose of image segmentation. …”
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Monograph -
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The image was then segmented into smaller parts using pixel-region-based image segmentation method. …”
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Thesis -
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Development of a new algorithm for segmentation of flotation froth images
Published 2014“…In the paper, the marker-based watershed method is modified to prevent oversegmentation of large bubbles. …”
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Fast marching method and modified features fusion in enhanced dynamic hand gesture segmentation and detection method under complicated background
Published 2018“…Quantitative measurement was performed for evaluating hand gesture segmentation algorithm. Besides, qualitative measurement was done to conduct a comparison based on segmentation accuracy with previous studies. …”
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Image enhancement and segmentation on simultaneous latent fingerprint detection
Published 2015“…This thesis presents an algorithm to segment individual fingerprints for SLF image. …”
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Thesis -
14
Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting
Published 2020“…All these matters contributed to the uncertainty in load demand forecasting. This paper modifies the classical fuzzy time series (FTS) algorithm by applying weighted subsethood based algorithm (WSBA) in FTS algorithm using segmented electricity load demand time series data. …”
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15
Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management
Published 2024“…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments
Published 2018“…In the proposed TVS, a modified candidate segment selection technique is initially employed to determine the candidate segments from the entire video. …”
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Thesis -
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Learning programming from source code examples is a common behavior among novices. …”
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Microcrack Detection And Noise Reduction In Integrated Circuit Packages
Published 2018“…Three algorithms are tested and evaluated in terms of microcrack detection and noise reduction which are probability based thresholding, histogram equalization, and modified Perona-Malik’s anisotropic diffusion methods. …”
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Monograph -
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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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