Search Results - (( feature extraction learning algorithm ) OR ( java simulation optimization algorithm ))
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1
Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Extending the concept of ensemble classifiers, this research applies the concept on the feature extraction and feature selection steps too, creating a multilayered ensemble of the three main tasks in machine learning sentiment analysis. …”
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2
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Feature extraction and selection reduces the number of features. …”
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3
Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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5
Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier
Published 2013“…FP-Growth (frequent pattern growth) algorithm was employed as a feature extraction technique. …”
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6
Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan
Published 2014“…The back-propagation learning algorithm is employed in the multi-layer neural network classifier. …”
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7
Postprocessing algorithm for security features extraction
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Feature extraction and supervised learning for volatile organic compounds gas recognition
Published 2023“…This research project aims to investigate effective feature extraction techniques that can be employed as discriminative features for machine learning algorithms. …”
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Context-driven satire detection with deep learning
Published 2022“…It is the study of extracting the most optimal features by using a deep learning architecture combined with carefully handcrafted contextual features. …”
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10
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa
Published 2020“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
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12
Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…Static analysis is where the static features are examined. Too many features used, features extraction time consuming and the reliability of accuracy result by various machine learning algorithm are the main issues spotted in static analysis approach. …”
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13
Feature extraction using neocognitron learning in hierarchical temporary memory
Published 2015“…Hierarchical Temporal Memory (HTM) serves as a practical implementation of the memory prediction theory.In order to obtain the optimum accuracy in pattern recognition, it is crucial to apply an appropriate learning algorithm for the feature extraction step of the HTM.This study proposes the use of neocognitron learning in extracting features of the pattern for image recognition.The integration of neocognitron into HTM addresses both the scale and time issues of the HTM. …”
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Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction
Published 2019“…The extracted features are then fed into the machine learning algorithm for classification process. …”
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15
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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16
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. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
Published 2023“…Extraction; Feature extraction; Image denoising; Image segmentation; Classification technique; Feature extraction and classification; Feature extraction techniques; Features extraction; Images processing; Machine learning algorithms; Machine learning methods; Research areas; Sensory system; Visual sensory; Image classification…”
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Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework
Published 2022“…Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023“…Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms…”
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