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  1. 1

    Brain tumor image segmentation using deep learning approach by Darshan, Suresh

    Published 2022
    “…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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    Article
  4. 4

    Automatic attendance system using face recognition with deep learning algorithm by Al-Amoudi, Ibrahim, Rosdiyana, Samad, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Pebrianti, Dwi

    Published 2022
    “…A GUI has been made to simplify the usage of the system. The face recognition system has been developed using a combination of two deep learning algorithms: Multi-Task Cascaded Convolutional Neural Network (MTCNN) and FaceNet. …”
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  5. 5

    Automatic attendance system using face recognition with deep learning algorithm by Al-Amoudi, Ibrahim, Rosdiyana, Samad, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Pebrianti, Dwi

    Published 2022
    “…A GUI has been made to simplify the usage of the system. The face recognition system has been developed using a combination of two deep learning algorithms: Multi-Task Cascaded Convolutional Neural Network (MTCNN) and FaceNet. …”
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  6. 6

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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  7. 7

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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    Article
  8. 8

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    Thesis
  9. 9

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…In this paper, the Alpha Beta filter has been used to predict the indoor Temperature, illumination, and air quality and remove noise from the data. We applied a deep extreme learning machine approach to predict the user parameters. …”
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  10. 10

    Depression Detection in Tweets from Urban Cities of Malaysia using Deep Learning by Priya Sri, E.K., Savita, K.S., Zaffar, M.

    Published 2021
    “…Therefore, the research entails on how the problem statement of this project on developing an algorithm that can predict text- based depression symptoms using deep learning and Natural Language Processing (NLP) can be achieved. …”
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  11. 11

    Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques by Muhadi, Nur 'Atirah

    Published 2022
    “…Hence, deep learning technique was chosen for water segmentation procedure in this work. …”
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    Thesis
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    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

    Published 2024
    “…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  16. 16

    Utilizing the Kolmogorov-Arnold Networks for chiller energy consumption prediction in commercial building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Muhammad Salihin, Saealal, Mohd Mawardi, Saari, Abu Zaharin, Ahmad

    Published 2024
    “…The methodology involves comparing KAN's performance with Artificial Neural Networks (NN) and a hybrid metaheuristic algorithm combined with deep learning, namely the Teaching-Learning-Based Optimization with Deep Learning (TLBO-DL). …”
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  17. 17

    Utilizing the Kolmogorov-Arnold Networks for chiller energy consumption prediction in commercial building by Sulaiman, Mohd Herwan, Mustaffa, Zuriani, Saealal, Muhammad Salihin, Saari, Mohd Mawardi, Ahmad, Abu Zaharin

    Published 2024
    “…The methodology involves comparing KAN’s performance with Artificial Neural Networks (NN) and a hybrid metaheuristic algorithm combined with deep learning, namely the Teaching-Learning-Based Optimization with Deep Learning (TLBO-DL). …”
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  18. 18

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…Fortunately, these issues can be addressed with machine learning methods such as deep learning(DL) due to its capacity in modeling highly non-linear phenomena, powerful generalization capability, and fast run-time. …”
    text::Thesis
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    A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework by Bari, Bifta Sama, Islam, Md Nahidul, Rashid, Mamunur, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Musa, Rabiu Muazu, Ahmad Fakhri, Ab. Nasir, Majeed, Anwar P.P. Abdul

    Published 2021
    “…The robustness of the Faster R-CNN model is enhanced by training the model with publicly available online and own real-field rice leaf datasets. The proposed deep-learning-based approach was observed to be effective in the automatic diagnosis of three discriminative rice leaf diseases including rice blast, brown spot, and hispa with an accuracy of 98.09%, 98.85%, and 99.17% respectively. …”
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  20. 20

    Anomaly detection for vision-based inspection by Chew, Yan Zhe

    Published 2022
    “…Tests were conducted on the MVTec Anomaly Detection dataset, which is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. The algorithms that were used for the conventional approach are Template Matching, Structural Similarity Index, Scale Invariant Feature-Transform and Oriented FAST and Rotated BRIEF, whereas the deep learning models that were used for the modern approach are Patch Distribution Modelling (PaDiM) and PatchCore. …”
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    Final Year Project / Dissertation / Thesis