Search Results - ((canny algorithm) OR (((learning algorithm) OR (means algorithm))))
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Modified canny edge detection technique for identifying endpoints
Published 2022“…Results have shown that, visually, our method has fewer discontinued edges when compared to Canny. Also, the mean square error of our method is lower than traditional Canny, indicating that our technique produces edge images that are more accurate than the traditional Canny.…”
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Conference or Workshop Item -
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Modified canny edge detection technique for joining discontinued edges
Published 2021“…Results have shown that, visually, our method has fewer discontinued edges when compared to Canny. Also, the mean square error of our method is lower than traditional Canny, indicating that our technique produces edge images that are more accurate than the traditional Canny.…”
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Proceedings -
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On the use of edge features and exponential decaying number of nodes in the hidden layers for handwritten signature recognition
Published 2018“…In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. …”
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Article -
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Development of offline handwritten signature authentication using artificial neural network
Published 2018“…As part of the feature extraction, two image filters were used, i.e. Canny edge detector and averaging filter. A feedforward neural network with 1 hidden layer was trained using backpropagation algorithm. …”
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Proceeding Paper -
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Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…A machine learning algorithms, SVM have been used to build species identification models. …”
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Undergraduate Final Project Report -
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Video colorization using canny optimization technique / Irwin Kevin Mueson
Published 2016“…Colorization process will be using the technique of Canny Optimization method. This is a hybrid technique from Colorization using Optimization, which was modified and improved the algorithms by adding Canny Edge Detection to improve the colorization process on the grayscale image or frames. …”
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Thesis -
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”
Conference Paper -
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Automatic Detection of Damaged Roads and Lane Detection using Deep Learning
Published 2025“…This project introduces an automated system for detecting road surface damages and identifying lane markings using Deep Learning, YOLO (You Only Look Once), and Canny edge detection. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Thesis -
10
Utilization of canny and velocity bunching algorithms for modelling shoreline change
Published 2006“…This paper introduces new method for simulating shoreline change from multi-SAR data. Edge detection algorithm such as Canny algorithm is implemented to identify shoreline. …”
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Conference or Workshop Item -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach
Published 2023“…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”
Article -
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management
Published 2024Subjects:Article -
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
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Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning
Published 2023“…Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering…”
Conference Paper -
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MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters
Published 2012“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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Integrated bisect K-means and firefly algorithm for hierarchical text clustering
Published 2016“…Such a result indicates that the proposed Bisect FA is a competitive algorithm for unsupervised learning.…”
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AUTOMATED CERVICAL CELL NUCLEI SEGMENTATION BASED ON MULTILAYER UNSUPERVISED CLUSTERING ALGORITHM AND MORPHOLOGICAL APPROACH
Published 2025“…The research aims to develop an algorithm for autonomously segmenting the nucleus of cervical cells to aid in diagnosis and future research. …”
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