Search Results - (( java segmentation using algorithm ) OR ( parameter deviation tree algorithm ))
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1
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…Here, a robust stopping rule for the cluster tree base on the median and median absolute deviation (MAD) of the tree heights is proposed. …”
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2
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Thus, it has been found that Satari’s algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…Thus, it has been found that Satari’s algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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4
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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5
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Thus, it has been found that Satari's algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. …”
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7
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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8
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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