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    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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    Thesis
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    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
    “…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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    Article
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    VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING by ONG KANG WEI, ONG KANG WEI, LOH SER LEE, LOH SER LEE

    Published 2022
    “…The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. …”
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    Article
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    Fuzzy C-Means with Improved Chebyshev Distance for Multi-Labelled Data by Mousa, Aseel, Yusof, Yuhanis

    Published 2018
    “…Fuzzy C-Means (FCM) is one of the most well-known clustering algorithms, nevertheless its performance has been limited by the utilization of Euclidean as its distance metric.Even though there exist studies that applied FCM with other distance metrics such as Manhattan, Minkowski and Chebyshev, its performance can still be argued particularly on multi-label data.Various applications rely on data points that can be grouped into more than one class and this includes protein function classification and image annotation.This study proposes the employment of FCM that is implement using an improved Chebyshev distance metric.The proposed work eliminates correlation in data points and improve performance of clustering.The results show that the proposed FCM improves the performance of clustering as it produces minimum objective function value and with less iteration count. …”
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    Article
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    A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

    Published 2023
    “…We hypothesized that revealing the implicit meaning of an idiom and using it as a feature may improve the sentiment classification results. …”
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    Final Year Project / Dissertation / Thesis
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    AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION by LAW, JIN MING

    Published 2022
    “…DenseNet-201 model is proposed as the base network to perform insulator fault detection autonomously. An algorithm with DenseNet-201 backbone consisting of two branches which are class label classification and bounding box regression is developed. …”
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    Final Year Project Report / IMRAD
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    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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    Thesis
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    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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    Thesis
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    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
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    Thesis
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    Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm by Wang, Xinming, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Mohd Idris Shah

    Published 2023
    “…Both the models effectively annotate and predict the leaf disease with good confidence score for each class. The other classification metrics like Precision, F1- score, Mean Average Precision, and recall also shows competitive results. …”
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    Article
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    Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

    Published 2024
    “…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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    Article
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    Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

    Published 2024
    “…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
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    Thesis
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