Search Results - (( using vectorization learning algorithm ) OR ( code classification based algorithm ))
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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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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Final Year Project / Dissertation / Thesis -
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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5
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Proceeding Paper -
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Phishing image spam classification research trends: Survey and open issues
Published 2020“…Low-level and image metadata are the most widely used features set. The methods of image spam classification as identified in this study are supervised machine learning, unsupervised machine learning, semi-supervised machine learning, content-based and statistical learning. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
Published 2024“…Traditional machine learning algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Trees (DT), and Support Vector Machines (SVM) have been employed to mitigate this challenge. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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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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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…Most of the algorithms got promising results and classify packets based on DSCP accurately. …”
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Source code classification using latent semantic indexing with structural and frequency term weighting
Published 2012“…This research proposes a Latent Semantic Indexing classifier that integrates information structural and frequency of terms in its weighting scheme.The content terms are identified by extracting words in the source code program. Based on the undertaken experiment the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…In video coding, research is focused on the development of fast motion estimation (ME) algorithms while keeping the coding distortion as small as possible. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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Software Classification Using Structure-Based Descriptors
Published 2009“…A total of 2800 programs have been used during the training process while two different datasets of size (28) were used for testing. Based on the undertaken experiment, the IBK algorithm is noted to generate the highest classification accuracy (74.8%) compared to several other algorithms provided in the Weka tool. …”
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