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  1. 1
    Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul

    Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul by Tom´As, Maul

    Published 2006
    “…Following this, at the formational level, various local mechanisms are investigated in the context of the biological development of the proposed neural architectures. It is shown that simple local rules, together with visual experience, such as that provided by dynamic images, are sufficient for the development of the neural architectures. …”
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  2. 2
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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  3. 3
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  4. 4
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…This approach tried to overcome the limitations of the manual method and traditional algorithm, which tends to fail with the diverse dataset, diverse visual features, and scalability. …”
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  5. 5
    Distracted driver detection with deep convolution neural networks

    Distracted driver detection with deep convolution neural networks by Basubeit, Omar Gumaan Saleh

    Published 2023
    “…This project aims to develop a python algorithm to detect the distracted activities while driving. …”
    text::Final Year Project
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  6. 6
    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment

    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
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  7. 7
    Fingerprint recognition using neural networks / Kennie Yeoh Eng Hoe

    Fingerprint recognition using neural networks / Kennie Yeoh Eng Hoe by Kennie Yeoh , Eng Hoe

    Published 2001
    “…Alternatively, patch-matching algorithm was developed in success of the Fourier Transform method when results -were not favorable to it. …”
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  8. 8
    BMI using spectral energy entropy for colour visual tasks

    BMI using spectral energy entropy for colour visual tasks by Divakar, Purushothaman, Paulraj, Murugesa Pandiyan, Prof. Madya Dr., Abdul Hamid, Adom, Dr., Hema, Chengalvarayan Radhakrishnamurthy

    Published 2012
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  9. 9
    Visual Crowd Counting System Using Deep Learning

    Visual Crowd Counting System Using Deep Learning by Mohd Wafi Nazrul Adam, Mohd Ridhwan Oxley Adam

    Published 2021
    “…This project is about developing a visual crowd counting system using deep learning. …”
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  10. 10
    Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques

    Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques by Ahmed Sabit, Hakilo

    Published 2006
    “…A neural network based flow regime identifier program is developed in Matlab environment. …”
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  11. 11
    Image quality assessment using Elman neural network model

    Image quality assessment using Elman neural network model by Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Palaniappan, Rajkumar, Mohd Shuhanaz, Zanar Azalan

    Published 2012
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  12. 12
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
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  13. 13
    Data mining based damage identification using imperialist competitive algorithm and artificial neural network

    Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

    Published 2018
    “…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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  14. 14
    Moving detection using cellular neural network (CNN)

    Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

    Published 2008
    “…The algorithm created is used to detect the ball in the images. …”
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  15. 15
    Color recognition wearable device using machine learning for visually impaired person

    Color recognition wearable device using machine learning for visually impaired person by Bolad, Tarek Mohamed, Nik Hashim, Nik Nur Wahidah, Mohamad Hanif, Noor Hazrin Hany

    Published 2018
    “…The user can also hear the name of the color along with ‘feeling’ the vibration. Two algorithms were used to distinguish between colors; RGB to HSV color conversion in comparison with neural network and decision tree based machine learning algorithms. …”
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  16. 16
    A random search based effective algorithm for pairwise test data generation

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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  17. 17
    Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution

    Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

    Published 2006
    “…The mutual information algorithms used in this work has been developed and experimented in the system and has proven to yield more accurate and stable results than other algorithms. …”
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  18. 18
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  19. 19
    EasyA: Easy and effective way to generate pairwise test data

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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  20. 20
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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