Search Results - (( parameter extraction learning algorithm ) OR ( java application stemming algorithm ))

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    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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    Thesis
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    Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach by Janai, Muhammad Asyraf, Woon, Kai Lin, Chan, Chee Seng

    Published 2018
    “…This study demonstrates the applicability of machine learning algorithm in extracting underlying complex correlations in blue PhOLEDs.…”
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    Article
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    Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD) by Gilani Mohamed, Mohamed Ahmed

    Published 2022
    “…The algorithm will be able to identify the parameters, such as the number of pixels, area pixels, and mean value, by extracting the hippocampal shape. …”
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    Thesis
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    Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

    Published 2021
    “…Too many features used, features extraction time consuming and the reliability of accuracy result by various machine learning algorithm are the main issues spotted in static analysis approach. …”
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    Thesis
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    Deep Learning Based Face Attributes Recognition by Saidi, Mohamad Hazim

    Published 2018
    “…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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    Monograph
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    Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

    Published 2018
    “…In addition, the results also showed that the proposed hierarchical classification method could extract geometric road elements with an average error rate of 6.25% for slope parameter and 6.65% for superelevation parameter, and it is transferable to other regions of similar environments. …”
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    Thesis
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    Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification by Hakim, S.J.S., Abdul Razak, H.

    Published 2013
    “…However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. …”
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    Article
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    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…Data mining (DM) is a novel data extraction technology which can employ for development of inverse analysis. …”
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    Thesis
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    Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning by Usman F., Nanda, Sumantyo J.T.S.

    Published 2023
    “…Overall, the four machine learning algorithms have outstanding performance, with a coefficient determinant of more than 0.9. …”
    Article
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    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

    Published 2020
    “…Thus, by enhancing the classification techniques in OBIA, building extraction accuracy using ML algorithms for medium resolution images can be improved and the expenses also can be reduced indirectly.…”
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    Thesis
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    Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

    Published 2023
    “…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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    Final Year Project Report / IMRAD
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    Smart diagnosis of long bone tumor / Mazni Parimin by Parimin, Mazni

    Published 2005
    “…Here, backpropagation training algorithm will be used and network parameters will be set. …”
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    Student Project
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    A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks by Azeez, Omer Saud, M. Shafri, Helmi Z., Alias, Aidi Hizami, Haron, Nuzul Azam

    Published 2022
    “…This paper presents a novel approach for combining convolutional neural networks (CNN) with OBIA based on joint optimization of segmentation parameters and deep feature extraction. A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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    Article
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    Computational extraction of dielectric properties from transmission and/or reflection coefficients: A survey by Nur Sofia Idayu, Didik Aprianto, Nurfarhana, Mustafa, Mohd Faizal, Jamlos, Kitazawa, Toshihide, Mohamad Shaiful, Abdul Karim

    Published 2024
    “…The overview of conventional measuring techniques – free space measurement, transmission line, resonant methods – and the conversion of the scattering parameters method to dielectric properties such as analytical, numerical analysis, and machine learning techniques, are being explored briefly. …”
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    Article
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    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
    “…The efficiency of the proposed methods is compared with the first and second order optimisation method by means of simulation on UCI Machine Learning Repository, Knowledge Extraction Evolutionary Learning and Kaggle dataset. …”
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    Thesis
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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    Thesis