Search Results - (( based evaluation method algorithm ) OR ( pattern extraction tree algorithm ))
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1
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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Thesis -
2
Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
3
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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4
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…From the enriched GO tree, the BTreeBicluster algorithm is applied during the clustering process. …”
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Monograph -
7
Determination of tree height based on tree crown using algorithm derived from UAV imagery / Suzanah Abdullah ... [et al.]
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Conference or Workshop Item -
8
An extended ID3 decision tree algorithm for spatial data
Published 2011“…It is because spatial data mining algorithms have to consider not only objects of interest itself but also neighbours of the objects in order to extract useful and interesting patterns. …”
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Conference or Workshop Item -
9
Improving mining efficiency: A new scheme for extracting association rules
Published 2009“…In the age of information technology, the amount of accumulated data is tremendous. Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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10
Coronary artery segmentation in angiograms with pattern recognition techniques - a survey
Published 2013“…There are lots of techniques and algorithms proposed for extracting coronary arteries in angiograms. …”
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11
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The algorithm involved the construction of the nodes of a lexicographic tree that represent frequent patterns. …”
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Thesis -
12
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…This article discusses the fundamental assumptions, benefits, and limitations of some well-known pattern recognition algorithms including Principal Component Analysis (PCA), Kernel PCA, Successive Projection Algorithm (SPA), Genetic Algorithm (GA), Partial Least Square Regression (PLS-R), Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Partial Least Square-Discriminant Analysis (PLS-DA) and Artificial Neural Network (ANN). …”
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Article -
14
Image Stitching Of Aerial Footage
Published 2021“…The images are warped to the key frame of the footage to generate a stitched image by using the computed homography. The algorithm performance is evaluated using the Orchard datasets, consisting of L-shape flight pattern and lawnmower flight pattern. …”
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Final Year Project / Dissertation / Thesis -
15
Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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16
Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In this research, another modification of Fuzzy Decision Tree (FDT) classification techniques called predictive FDT is presented that aims to combine symbolic decision trees in data classification with approximate reasoning offered by fuzzy representation. …”
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17
Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…The proposed model validated the testing dataset of three palm tree regions with mature, young, and mixed mature and young palm trees. …”
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18
Image segmentation for songket motif / Zati Iwani Zaharudin
Published 2007“…This research will cover on partitioning twenty collection of songket pattern into a number of songket motifs. This paper will cover on comparison of three algorithms of image segmentation, determining which algorithm is more accurate in order to extract songket motifs and a prototype of image segmentation tool using the accurate algorithm determined. …”
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Thesis -
19
Finger Motion In Classifying Offline Handwriting Patterns
Published 2017“…This study involves the features extractions from handwriting patterns of 30 subjects with recorded videos of finger movements during writings. …”
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Monograph -
20
Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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