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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023)

    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

    Published 2025
    “…Additionally, we propose a novel framework that seamlessly merges meta-heuristic algorithms into deep learning paradigms, aiming to enhance performance and efficiency in addressing energy-related problems. …”
    Review
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  3. 3
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  4. 4
    Deep reinforcement learning with robust deep deterministic policy gradient

    Deep reinforcement learning with robust deep deterministic policy gradient by Teckchai Tiong, Ismail Saad, Kenneth Tze Kin Teo, Herwansyah Lago

    Published 2020
    “…Recently, Deep Deterministic Policy Gradient (DDPG) is a popular deep reinforcement learning algorithms applied to continuous control problems like autonomous driving and robotics. …”
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  5. 5
    Deep reinforcement learning approaches for multi-objective problem in Recommender Systems

    Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

    Published 2022
    “…In the performance comparison between proposed deep reinforcement learning with evolutionary algorithm, despite one of the variants of evolutionary algorithm has good performance in precision, it has rather weak performance in term of novelty and diversity. …”
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  6. 6
    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications

    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

    Published 2020
    “…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. …”
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  7. 7
    Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail

    Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail by ZhongMing, Liao, Ismail, Azlan

    Published 2023
    “…In terms of the computer vision field, deep learning has achieved remarkable results. It has broken through many complex problems that are difficult to be solved by traditional algorithms. …”
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  8. 8
    Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification

    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
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  9. 9
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  10. 10
    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm

    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

    Published 2023
    “…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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  11. 11
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  12. 12
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  13. 13
    Multiobjective deep reinforcement learning for recommendation systems

    Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

    Published 2022
    “…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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  14. 14
    Multi-objective deep reinforcement learning for recommendation systems

    Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

    Published 2022
    “…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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  15. 15
    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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  16. 16
    Overhead view based person counting using deep learning

    Overhead view based person counting using deep learning by Kaw, Chee Zhao

    Published 2022
    “…However, the counting accuracy of Centroid Tracking algorithm is about 22.2% lower than the DeepSORT tracking algorithm. …”
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  17. 17
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    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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  18. 18
    Machine learning and deep learning approaches for cybersecurity: a review

    Machine learning and deep learning approaches for cybersecurity: a review by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

    Published 2022
    “…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
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  19. 19
    Traffic signal control with deep reinforcement learning

    Traffic signal control with deep reinforcement learning by Lau, Joseph Yi Zhe

    Published 2025
    “…With numerous efforts and research in this area, the methods have evolved from transportation theory to deep reinforcement learning (DRL) approaches over the years. …”
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  20. 20
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
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