Search Results - (( code classification learning algorithm ) OR ( based optimization window 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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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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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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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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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm
Published 2014“…This paper proposes an optimal method to suppress the noise with high density properly based on a nonlinear filter and decision-based approach. …”
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Conference or Workshop Item -
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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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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. …”
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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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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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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks
Published 2022“…The second part proposes an optimized flexible window-overlapping scheduling (OFWOS) algorithm that optimizes the offset difference ( ) between the samepriority TT windows in the adjacent nodes. …”
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Thesis -
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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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Classification of machine learning engines using latent semantic indexing
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Conference or Workshop Item -
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Enhanced local disparity map algorithm segment-side window-based cost aggregation and refinement
Published 2025“…This paper introduces a Segment-Side Window based (SSW) stereo matching algorithm that combines Truncated Absolute Difference (TAD), Gradient Magnitude (GM), and Census Transform (CT) to build a robust cost volume. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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