Search Results - (( using function learning algorithm ) OR ( basic detection model algorithm ))
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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2
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RSNN implements a novel approximation transform. The basic design for the network is provided together with the learning rules. …”
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3
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…Using this method, the learning time is shorten, and thus, the DDoS backscatter can be detected fast. …”
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4
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The derived model was rigorously compared to four models, including basic ELM, basic FLN, Reduce Kernel ELM (RK-ELM), and RK-FLN. …”
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5
The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional
Published 2006“…The first is enhanced thinning algorithm that is used to thin the sketch while maintaining its topology and basic shape. …”
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WEBCAM MOTION DETECTION USINGVISUAL BASIC
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Thalassaemia detection using CBR Algorithm via mobile device
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9
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…Our developed model has been compared against a basic ELM. PSO-ELM has outperformed a basic model in the testing accuracy.…”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
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12
Shot boundary detection based on orthogonal polynomial
Published 2019“…The design of SBD algorithms developed from simple feature comparison to rigorous probabilistic and using of complex models. …”
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13
Training functional link neural network with ant lion optimizer
Published 2020“…Functional Link Neural Network (FLNN) has becoming as an important tool used in machine learning due to its modest architecture. …”
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14
Development of control algorithm for a new 12s-6p single phase field excited flux switching motor
Published 2020“…For position detection, algorithms merely need a basic infrared transceiver sensor. …”
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15
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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16
A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
17
Enhanced algorithms for three-dimensional object interpreter
Published 2004“…In the first phase, two algorithms were proposed. The first is enhanced thinning algorithm that is used to thin the sketch while maintaining its topology and basic shape. …”
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18
An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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19
Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach
Published 2010“…Developing such a model from basic laws is a complicated and time consuming task. …”
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20
Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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