Showing 61 - 80 results of 210 for search '(( elements b algorithm ) OR ((( data code algorithm ) OR ( data detection algorithm ))))', query time: 0.13s Refine Results
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    Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

    Published 2023
    “…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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  4. 64

    Capturing outline of fonts using genetic algorithm and splines by Sarfraz, M.

    Published 2001
    “…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. We also incorporate a corner detection algorithm to detect significant points which are necessary to capture a pleasant looking spline fitting for shapes such as fonts. …”
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    article
  5. 65

    GenDE: A CRF-Based Data Extractor by Kayed, Mohammed

    Published 2020
    “…Web site schema detection and data extraction from the Deep Web have been studied a lot. …”
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    Data redundancy management for leaf-edges in connected environments by Mansour, Elio

    Published 2022
    “…DRMF considers both static and mobile edge devices, and provides two algorithms for temporal and spatio-temporal redundancy detection. …”
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    article
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    Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

    Published 2016
    “…Classification has three main components: the classification algorithm, the pre-classified data (training data) and the un-classified data (testing data). …”
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    masterThesis
  9. 69

    Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

    Published 2023
    “…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
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    Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

    Published 2021
    “…Overall, studies that used smaller data sets reported higher accuracy.</p><h3>Conclusions</h3><p dir="ltr">This paper examined multiple AI-based skin cancer detection models. …”
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    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    Published 2023
    “…Therefore, this study aims to evaluate several versions of Recurrent Neural Networks (RNNs) and Feedforward Neural Networks (FNNs) for detecting cyberbullying in the Arabic language. Although these algorithms are widely used in text classification and outperform the performance of classical classifiers, many have been extensively investigated in other domains such as sentiment analysis and dialect identification, as well as cyberbullying detection in English text. …”
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    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

    Published 2006
    “…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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    article
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    Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

    Published 2022
    “…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”
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    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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