Showing 81 - 100 results of 151 for search '(fact OR face) research random three algorithm', query time: 0.21s Refine Results
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    Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

    Published 2024-08-01
    “…To isolate and quantify the crack region, this research combines image thresholding, morphological operations, and contour detection with the convex hulls method and forms a novel algorithm. …”
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    Article
  3. 83

    Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

    Published 2025-08-01
    “…This study employed local interpretable model-agnostic explanations (LIME) and SHapley Additive exPlanations (SHAP) to demystify the endotype prediction model. A random forest model was built to assess an individual's risk for nephropathy and retinopathy based on individual risk algorithms.…”
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    Fault Detection in Photovoltaic Systems Using a Machine Learning Approach by Jossias Zwirtes, Fausto Bastos Libano, Luis Alvaro de Lima Silva, and Edison Pignaton de Freitas

    Published 2025-01-01
    “…The proposed fault detection solutions rely on analyzing different algorithms, including Support Vector Machine, Artificial Neural Network, Random Forest, Decision Tree, and Logistic Regression. …”
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    A framework of crop water productivity estimation from UAV observations: A case study of summer maize by Minghan Cheng, Ni Song, Josep Penuelas, Matthew F. McCabe, Xiyun Jiao, Yuping Lv, Chengming Sun, Xiuliang Jin

    Published 2025-08-01
    “…To address this challenge, our research develops an innovative UAV-based monitoring framework through systematic integration of long-term multispectral/thermal infrared observations with multi-model fusion: (1) Surface Energy Balance Algorithm for Land (SEBAL) and FAO-56 Penman-Monteith models for evapotranspiration (ET) estimation; (2) Random Forest algorithm incorporating four phenotypical growth indicators for yield estimation, ultimately enabling CWP quantification. …”
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    Employees’ Satisfaction and Sentiment Analysis toward BERSATU Application by Ayub Prasetyo, Hotniar Siringoringo, Firda Amalia

    Published 2025-02-01
    “…Therefore, the research aims to analyze sentiment of user review on “BERSATU” application, using various algorithm classification and modeling topic. …”
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    Cowpea genetic diversity, population structure and genome-wide association studies in Malawi: insights for breeding programs by Michael M. Chipeta, John Kafwambira, Esnart Yohane

    Published 2025-01-01
    “…The study assessed the effects of genotype, location, and their interactions on morphological traits. The Fixed and Random Model Circulating Probability Unification (FarmCPU) algorithm was used to identify significant MTAs.ResultsThe morphological traits showed significant genotype, location, and interaction effects. …”
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    UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

    Published 2024-12-01
    “…The results indicate that the Random Forest (RF) model outperforms the other four ML algorithms, achieving an overall accuracy (OA) of 89.29% and a Kappa coefficient of 0.8852. …”
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    ProCAPTCHA: A profile-based CAPTCHA for personal password authentication. by Nilobon Nanglae, Pattarasinee Bhattarakosol

    Published 2024-01-01
    “…ProCAPTCHA leverages keystroke dynamics and personal information to create unique CAPTCHAs that are difficult for intruders to solve. ProCAPTCHA's algorithm generates CAPTCHA based on the user's profile data, ensuring randomness and uniqueness for each login. …”
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