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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  4. 4
    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu

    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…The methodology used in the development of this project is basically based on the eight major steps. There are problem assessment, data acquisition, cropping, pre-processing, design, training, testing and documentation. …”
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  5. 5
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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  6. 6
    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal

    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…For the Feed Forward, Recurrent and Self Organizing Map Networks there are the Neuron Model, Basic Architecture and Training Algorithm. The demonstrations are included each every topic. …”
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  7. 7
    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning

    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

    Published 2023
    “…Furthermore, the study adopted the approximate dynamic learning rate update algorithm in the model training to realize the learning rate’s self-adaptation, ensure the model’s rapid convergence, and shorten the training time. …”
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  8. 8
    Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

    Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)... by Pradhan, Biswajeet, Mohammad Zare, Pourghasemi, Hamid Reza, Vafakhah, Mahdi

    Published 2013
    “…The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. …”
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  9. 9
    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…Multi-layer perceptron (MLP) neural network trained using backpropagation algorithm is used to segment the color image. …”
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  10. 10
    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier

    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah, Noorizan , Yahya

    Published 2013
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  11. 11
    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems

    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

    Published 2010
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  12. 12
    Review of deep convolution neural network in image classification

    Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

    Published 2017
    “…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
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  13. 13
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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  14. 14
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…Randomly select the m data set for conventional training algorithm. One more data (m+ 1) is entered to train the NN again. …”
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  15. 15
    Implementation of hashed cryptography algorithm based on cryptography message syntax

    Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

    Published 2019
    “…By the end of the research, the animation and animation system will be introduced to show the basic process of network enhancement with the automated learning system.…”
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  16. 16
    Neural Network – A Black Box Model

    Neural Network – A Black Box Model by Kuok, Kuok King, Chan, Chiu Po, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said, Chin Mei, Yun

    Published 2024
    “…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
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  17. 17
    A novel neuroscience-inspired architecture: for computer vision applications

    A novel neuroscience-inspired architecture: for computer vision applications by Hassan, Marwa Yousif, Khalifa, Othman Omran, Abu Talib, Azhar, Olanrewaju, Rashidah Funke, Hassan Abdalla Hashim, Aisha

    Published 2016
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  18. 18
    Image Splicing Detection With Constrained Convolutional Neural Network

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. Constrained CNN is basically a Deep Learning CNN model with its first layer weights being constrained so that it only extracts splicing manipulation features instead of object features. …”
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  19. 19
    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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  20. 20
    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy

    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

    Published 2022
    “…The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. …”
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