بدائل البحث:
extraction algorithm » detection algorithm (توسيع البحث)
features extraction » feature extraction (توسيع البحث)
يعرض 121 - 131 نتائج من 131 نتيجة بحث عن 'features extraction algorithm', وقت الاستعلام: 0.04s تنقيح النتائج
  1. 121

    Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives حسب Yassine Himeur (14158821)

    منشور في 2021
    "…Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …"
  2. 122

    A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies حسب Farideh Abdollahi (22303153)

    منشور في 2024
    "…The fingerprinting and descriptors are two commonly approach for polymer featurization. In terms of algorithms, <u>neural networks</u> (NNs), random forest (RF), and gaussian process regression (GPR) are among the most extensively applied methods. …"
  3. 123

    Arabic Hotel Reviews Sentiment Analysis Using Deep Learning حسب ALMANSOORI, MOHAMMAD

    منشور في 2023
    "…Our models utilized advanced text preprocessing, feature extraction, and classification algorithms to accurately predict sentiment polarity in Arabic hotel reviews. …"
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  4. 124

    Arabic text recognition حسب Haraty, Ramzi

    منشور في 2004
    "…In other words, character classification, especially handwritten Arabic characters, depends largely on contextual information, not only on topographic features extracted from these characters.…"
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    article
  5. 125

    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

    منشور في 2025
    "…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …"
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    article
  6. 126

    Data visualization and pattern discovery in IoT حسب Bektemirov, Abdukhamid

    منشور في 2025
    "…The given method is a combination of nonlinear optimization of features with the help of metaheuristic algorithms and sophisticated dimensionality reduction techniques to preserve the important information with reducing redundancy. …"
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  7. 127

    Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques حسب Amith Khandakar (14151981)

    منشور في 2022
    "…Classical machine learning algorithms with feature engineering and the convolutional neural network (CNN) with image enhancement techniques were extensively investigated to identify the best performing network for classifying thermograms. …"
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  9. 129

    Exploring new horizons in neuroscience disease detection through innovative visual signal analysis حسب Nisreen Said Amer (17984077)

    منشور في 2024
    "…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …"
  10. 130

    PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits حسب Hind Almerekhi (7434776)

    منشور في 2022
    "…This procedure entailed using our large-scale dataset to refine toxicity triggers' definition and build a trigger detection dataset using 991,806 conversation threads from the top 100 communities on Reddit. Then, we extracted a set of sentiment shift, topical shift, and context-based features from the trigger detection dataset, using them to build a dual embedding biLSTM neural network that achieved an AUC score of 0.789. …"
  11. 131