Search Results - (( parallel extraction method algorithm ) OR ( variable active learning algorithm ))

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  1. 1

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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    Final Year Project / Dissertation / Thesis
  2. 2

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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    Thesis
  3. 3

    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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    Thesis
  4. 4

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. …”
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    Thesis
  5. 5

    Robust partitioning and indexing for iris biometric database based on local features by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy

    Published 2018
    “…The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. …”
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    Article
  6. 6

    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…In parallel, handcrafted features are extracted using the modified gray level co-occurrence matrix (MGLCM) method. …”
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    Article
  7. 7

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
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  9. 9

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
  10. 10

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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    Thesis
  11. 11

    A new multi-frames watermarking technique for tamper detection and recovery by Khor, Hui Liang

    Published 2017
    “…The sequential multi-frames watermarking process could be speed up by two methods, first method was designed a speedy watermarking scheme algorithm (ROI-DR) in a single frame of medical image, and the second method was developed a new multi-frames watermarking scheme by adding parallelism component into sequential multi-frames watermarking process. …”
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    Thesis
  12. 12

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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    Article
  13. 13

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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    Article
  14. 14
  15. 15

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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    Thesis
  16. 16

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…The temperature, humidity and visibility attributes from the dataset has been extracted by the MapReduce Algorithm into structure data. …”
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    Thesis
  17. 17

    Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

    Published 2024
    “…The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.…”
    Proceedings Paper
  18. 18

    Classifying corporates default and non-default using machine learning Artificial Neural Network: multilayer perceptron / Nur Insyirah Mohamad Radzi, Murni Salina Rosidi and Nur Asy... by Mohamad Radzi, Nur Insyirah, Rosidi, Murni Salina, Zailand, Nur Asyura Izzati

    Published 2023
    “…Asset volatility is found to be the most significant independent variable. Therefore, ANN is a machine learning algorithm that uses multiple layers perceptron to solve complex problems and predict analytics.…”
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    Student Project
  19. 19

    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
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