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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective
Published 2019“…It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. …”
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2
Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy
Published 2023Subjects:Article -
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Fault classification in smart distribution network using support vector machine
Published 2023“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…Furthermore, the Support vector machine (SVM) and Linear discriminant analysis (LDA) machine learning for the hand posture classification based on the EMG signal pattern were investigated and compared in term of classification performance. …”
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Cyberbullying detection: a machine learning approach
Published 2022“…Those algorithms are used in the classification or regression model to predict an input. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…However, a few overlapped NIRs’ spectral data between healthy and infected samples require for further validation which chemometric and machine learning (ML) classification technique are chosen. …”
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Gender Classification: A Convolutional Neural Network Approach
Published 2016“…Unlike in conventional CNNs, we replace the convolution operation with cross-correlation, hence reducing the computational load. The network is trained using a second-order backpropagation learning algorithm with annealed global learning rates. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Development of vehicle detection and counting system for traffic analysis using computer vision
Published 2024“…Once the trained weights are ready a deep learning algorithm detection model is applied to detect and draw a bounding box on the vehicles. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud
Published 2008“…Step search (4SS), Diamond search (DS), Adaptive Rood Pattern Search (ARPS) and Cross-Diamond-Hexagonal search (CDHS). This algorithm basically employs two crossshaped search patterns consecutively in the very beginning steps and switch using diamond-shaped patterns. …”
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An enhanced minimum variance distortionless response beamformer techniques to reduce interference in array antenna system
Published 2017“…First, the zero-null constraint adds to the MVDR beamformer based on uniform linear antenna arrays. The proposed MVDRZN is based on reconstructing the excitation weight vector coefficients to enforcing the undesired signal energy equal to zero (or near zero) and the desired signal energy equal to one (unity gain). …”
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…This model is then to be used in the prototype tool development that is called 3De-ALPROV (Design Development Debug – Algorithm Program Visualization). The efficacy evaluation of the prototype is based on pre- and post- test of the students’ programming performance. …”
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An application of barnacles mating optimizer algorithm for combined economic and emission dispatch solution
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Analysis of the Flood Extent Extraction Model and the Natural Flood Influencing Factors: A GIS-based and Remote Sensing Analysis
Published 2013“…The purpose of this paper is to develop a flood extent extraction model based on Minimum Distance Algorithm and to overlay with the natural flood influencing factors considered herein in order to examine the effect of each factor in flood generation. …”
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A systematic review on emperor penguin optimizer
Published 2021“…To-date, EPO has slowly gaining considerable momentum owing to its successful adoption in many broad range of optimization problems, that is, from medical data classification, economic load dispatch problem, engineering design problems, face recognition, multilevel thresholding for color image segmentation, high-dimensional biomedical data analysis for microarray cancer classification, automatic feature selection, event recognition and summarization, smart grid system, and traffic management system to name a few. …”
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