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  1. 1

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…However, deep learning algorithms, such as deep belief networks showed promising results in many domains, especially in image processing. …”
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    Article
  2. 2

    Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

    Published 2021
    “…Studies published from 2015 to 2021 under the keywords (deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed. …”
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    Article
  3. 3

    Deep learning methods for facial expression recognition by Mohammad Masum Refat, Chowdhury, Zainul Azlan, Norsinnira

    Published 2019
    “…Different types of deep learning algorithms have been used for FER such as deep belief network (DBN) and convolutional neural network (CNN). …”
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    Proceeding Paper
  4. 4

    Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based by Saeed, Mamoon M, Saeed, Rashid A, Ali, Elmustafa Sayed, Mokhtar, Rania A, Khalifa, Othman Omran

    Published 2024
    “…This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G networks. …”
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    Proceeding Paper
  5. 5

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…In this study, the Deep Belief Network algorithm was optimized and constructed to design an effective NIDS anomaly model. …”
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    Thesis
  6. 6

    Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz

    Published 2019
    “…Imbalanced class data is a common issue faced in classification tasks. Deep Belief Networks (DBN) is a promising deep learning algorithm when learning from complex feature input. …”
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    Article
  7. 7

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
    “…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection by A. Mostafa, Salama, Al-Azzawi, Ziadoon Kamil Maseer, Bahaman, Nazrulazhar, Yusof, Robiah, Musa, Omar, Al-rimy, Bander Ali Saleh

    Published 2021
    “…The HW-DBN algorithm integrates an improved Gaussian–Bernoulli restricted Boltzmann machine (Deep GB-RBM) feature learning operator with a weighted deep neural networks (WDNN) classifier. …”
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    Article
  9. 9

    Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.

    Published 2023
    “…Backpropagation algorithms; Computation theory; Deep learning; Face recognition; Iterative methods; Knowledge acquisition; Machine learning; Neural networks; Biological learning; Convolutional neural network; DeepID; Extreme learning machine; Face Verification; Fast implementation; Feature mapping; Labeled faces in the wilds (LFW); Learning algorithms…”
    Article
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    A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

    Published 2023
    “…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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    Article
  12. 12

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

    Published 2023
    “…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”
    Article
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    An Improved Ensemble Deep Learning Model Based on CNN for Malicious Website Detection by Do N.Q., Selamat A., Lim K.C., Krejcar O.

    Published 2023
    “…Computer crime; Convolution; Convolutional neural networks; Cybersecurity; Learning algorithms; Learning systems; Recurrent neural networks; Bidirectional gated recurrent unit; Convolutional neural network; Cyber security; Deep learning; Learning models; Malicious website; Model-based OPC; Phishing detections; Phishing websites; Websites…”
    Conference Paper
  15. 15

    Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system by Balla, Asaad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Mubarak, Sinil

    Published 2022
    “…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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    Article
  16. 16

    A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

    Published 2023
    “…air quality; algorithm; artificial neural network; industrial development; literature review; machine learning; public health; time series; urbanization; air pollution; forecasting; human; time factor; Air Pollution; Deep Learning; Forecasting; Humans; Neural Networks, Computer; Time Factors…”
    Review
  17. 17

    Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization by Usmani, Usman Ahmad, Usmani, Mohammed Umar

    Published 2023
    “…It explores fundamental aspects such as network architectures, activation functions, and learning algorithms, analyzing their theoretical foundations. …”
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    Conference or Workshop Item
  18. 18

    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…Three deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are used to develop the prediction model. …”
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    Article
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