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    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

    Published 2021
    “…Some of the existing methods of segmentation are K-Means, Otsu’s, edge-based segmentation, watershed segmentation, region growing, mean shift, maxflow mincut (MFMC) graph cut and regional colour segmentation. …”
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    Thesis
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    Embedded car plate image recognition system by Moo Wui Hung

    Published 2008
    “…In order to speed up the image processing process, the system do not use complex algorithm such as Neural Network but use a simple algorithm such as template matching. …”
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    Learning Object
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    Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

    Published 2023
    “…In the future, enhancement of the segmentation using artificial neural networks will help in the earlier and more precise detection of brain tumors. …”
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    Article
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    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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    Thesis
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    Contactless palmprint verification using siamese networks by Ng, Jan Hui

    Published 2022
    “…The novelties of this project are the algorithm used to segment the feature abundant region of interest from the palm image, and also the usage of a custom-built Siamese Network utilising a state-of-the-art CNN called EfficientNet as the underlying feature extractor. …”
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    Final Year Project / Dissertation / Thesis
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    Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques by Pethuraj, Mohamed Shakeel, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

    Published 2022
    “…The gathered image noise is removed by applying the mean filter, and the affected regions are segmented with the help of the Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC)algorithm. …”
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    Article
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    Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography by Huddin, Azzam Basseri, Huddin, Aqilah Baseri, Tharek, Anas, Wan Zaki, Wan Mimi Diyana, Muda, Ahmad Sobri

    Published 2022
    “…The t-test analysis is performed between the sum squared error (SSE) of ICH measurements from the automated-ground truth and the conventional-ground truth. Results: The mean volumetric Dice similarity coefficient for the automated segmentation algorithm when tested against the ground truth, is 0.859±0.135. …”
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    Article
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    An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

    Published 1996
    “…Secondly, for the intelligent trajectory generation approach, the segmented tree neural networks for each link (inverse kinematics solution) and the randomness with fuzziness (coping the unstructured environment from the cost function) were used. …”
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    Thesis
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    A NOVEL FORWARD BACKWARD LINEAR PREDICTION ALGORITHM FOR SHORT TERM POWER LOAD FORECAST by BAHARUDIN, ZUHAIRI

    Published 2010
    “…The proposed AR-based algorithm divides long data record into short segments and searches for the AR coefficients that simultaneously model the data with the least means squared errors. …”
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    Thesis
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    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

    Published 2022
    “…The Random Forest algorithm was the best algorithm compared to the artificial neural network, which produced the highest R2 (0.998) and lowered RSME (55.067). …”
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    Thesis
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    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…On the other hand, existing stream data learning models with limited labelling have many limitations. Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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    Thesis
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    Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch by Fadilah, Norasyikin

    Published 2015
    “…The images are collected and analyzed using digital image processing techniques. k-means clustering algorithm is used to segment the image into two separate regions which are fruit and spike regions. …”
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    Thesis
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    Development of gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

    Published 2009
    “…The formant frequencies are obtained by finding a set of predictor coefficient that minimizes the mean square error over a short segment of speech waveform. …”
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    Learning Object
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