Search Results - (( co extraction process algorithm ) OR ( java implication based algorithm ))

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    Modelling semantic context for novelty detection in wildlife scenes by Yong, SP, Deng, JD, Purvis, MP

    Published 2010
    “…Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. …”
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    Conference or Workshop Item
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    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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    Article
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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
    “…This algorithm was compared to co-spectral plot method for labelling clusters the clusters generated in Landsat TM dataset. …”
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    Thesis
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    A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm S... by Osman, Khairuddin, Mohamad, Syahrul Hisham, Jaafar, Hazriq Izzuan

    Published 2013
    “…The features of the wood knot images are extracted using Gray Level Co-Occurrence Matrix. Binary Magnetic Optimization Algorithm is use to optimize the feature selection process. …”
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    Conference or Workshop Item
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    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…The textural features extracted are based on the first-order statistics and second-order statistics computed from grey level co-occurrence matrices (GLCM). …”
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    Final Year Project
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    Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba by Ghulam , Mujtaba

    Published 2018
    “…Moreover, support vector machines and random forest algorithms outperformed the four other algorithms. The proposed techniques are feasible and practical in determining the CoD from forensic autopsy reports and can assist pathologists to accurately and rapidly determine the CoD from autopsy findings. …”
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    Thesis
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    Image matching using relational graph representation by Lai, Chui Yen

    Published 2005
    “…Structural descriptions are consist of lines and interline relationship in the line-extracted image. Three conditions of inter-line relationship, namely ordering, intersection and co-linearity, were defined and derived in this study. …”
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    Thesis
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    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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    Thesis
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    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The second stage (i.e. feature extraction stage) extracts the features based on ROI using the grey-level co- occurrence matrix (GLCM). …”
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    Thesis
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    Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

    Published 2020
    “…The combination of Prewitt algorithm, Canny alogorithm, Gray-Level co-occurrence matrix will be used in SVM. …”
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    Undergraduate Final Project Report
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    Texture-based feature using multi-blocks gray level co-occurrence matrix for ethnicity identification by Mohd Zamri, Osman, M. A., Maarof, Mohd Foad, Rohani

    Published 2020
    “…The detected face then exploited by three proposed face block which are 1×1, 1×2 and 2×2. In the feature extraction process, a Grey Level Co-occurrence Matrix (GLCM) under different face blocks were employed. …”
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    Conference or Workshop Item
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    Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    Published 2022
    “…This technique is challenged by the nature of IoT technology and perceived data, as well as by human differences, which necessitated additional processing tasks to select significant features for the learning algorithms. …”
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    Article
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