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يعرض 1 - 20 نتائج من 58 نتيجة بحث عن 'based detection methodologies', وقت الاستعلام: 0.07s تنقيح النتائج
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    Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine حسب Debendra Muduli (20748758)

    منشور في 2024
    "…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …"
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    Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques حسب Ameema Zainab (16864263)

    منشور في 2020
    "…A dataset publicly available for a smart home, along with weather conditions, is used for the methodology validation. The proposed algorithm is used to detect the spamicity score of the connected IoT devices in the network. …"
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    Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection حسب Sulaiman Khan (12585349)

    منشور في 2023
    "…This research study presents a data fusion-based method for underwater salient object detection and ocean environment monitoring by utilizing a deep model.…"
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    Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

    منشور في 2023
    "…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …"
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    A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study حسب Masurkar, Faeez

    منشور في 2022
    "…Based on the obtained accuracy of the results, the proposed methodology has been found to be capable of inspecting rail track specimens in a completely non-contact manner with reasonably good accuracy…"
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    Artificial Intelligence for Skin Cancer Detection: Scoping Review حسب Abdulrahman Takiddin (14153181)

    منشور في 2021
    "…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…"
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    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts حسب ALSHAMSI, SUROUR

    منشور في 2022
    "…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …"
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    Fault Detection of Fuel Systems Using Polynomial Regression Profile Monitoring حسب Awad, Mahmoud

    منشور في 2016
    "…We present in this paper a new monitoring framework for smart fuel systems utilizing outlying observations detection and monitoring using ccharts. The traditional control charts based on the Hotelling's T2 statistic were deficient in detecting SFS anomalies and a new approach was necessary to isolate faulty profiles. …"
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    AI-driven wearable sensors for postoperative monitoring in surgical patients: A systematic review حسب Muhammad Mohsin Khan (22150360)

    منشور في 2025
    "…Traditional monitoring systems, based on periodic measurement of vital signs, often cannot detect subtle physiological changes that herald early clinical deterioration. …"
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    Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis حسب Marwa Qaraqe (10135172)

    منشور في 2024
    "…Moreover, the prevailing approach to crowd behavior recognition, which solely relies on the analysis of closed-circuit television (CCTV) footage and overlooks the integration of online social media video content, leads to a primarily reactive methodology. This paper proposes a crowd behavior detection framework based on the swin transformer architecture, which leverages crowd counting maps and optical flow maps to detect crowd behavior across various sizes and violence levels. …"