Search Results - (( java application modified algorithm ) OR ( basic extractions learning algorithm ))
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Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin
Published 2019“…Traditional learning-based boundary extraction algorithms classify each pixel edge separately and then get boundaries from the local decisions of a classifier. …”
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Thesis -
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Direct approach for mining association rules from structured XML data
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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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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…The purpose of the project is basically to extract and identify each object elements in an image picture. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…The algorithm is implemented as a plugin. It does not interfere with the web application original code. …”
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Conference or Workshop Item -
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Monograph -
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Review of deep convolution neural network in image classification
Published 2017“…This paper first introduces the rise and development of deep learning and convolution neural network, and summarizes the basic model structure, convolution feature extraction and pooling operation of convolution neural network. …”
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i-ManGoeS
Published 2017“…Then, the features are extracted from the object. Finally fuzzy learning algorithm will formulate the object features to classify the children activity and satisfaction.…”
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Book Section -
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DSC766: Text Analytics / College of Computing, Informatics and Mathematics
Published 2020“…However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. Student will learn the basic concepts, principles, and major algorithms in text mining and their potential applications.…”
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Teaching Resource -
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Simulation on Emotion Recognition for Autism Therapy
Published 2017“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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Final Year Project -
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A novel neuroscience-inspired architecture: for computer vision applications
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…The trained EBrC-Net is used to extract discriminative features. The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. …”
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Development of durian ontology from unstructured text and external knowledge source / Khairul Nurmazianna Ismail
Published 2014“…Thirdly, ontology elements from both ontology methods are extracted by using RDF Query Language. Ontology element extraction of manual ontology development consists of three processes namely ontology element selection, query construction and ontology element extracted. …”
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Thesis