Search Results - (( basic extraction learning algorithm ) OR ( java application matching algorithm ))

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    Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin by AmirHussin, 'Afina

    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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    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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    Thesis
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    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…The purpose of the project is basically to extract and identify each object elements in an image picture. …”
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    Thesis
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    Securing cloud data system (SCDS) for key exposure using AES algorithm by Thabet Albatol, Mohammed Samer Hasan

    Published 2021
    “…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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    Thesis
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    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    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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    Article
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    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    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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    Thesis
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    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    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 by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

    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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    Article
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    i-ManGoeS by Ahmad, Khairul Adilah, Abdul Malik, Anis Faradella

    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 by UiTM, 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 by Adzmi, Muhammad Azrin

    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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    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    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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    Thesis