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    Comparative Evaluation of AI-Based Multi-Spectral Imaging and PCR-Based Assays for Early Detection of <i>Botrytis cinerea</i> Infection on Pepper Plants by Dimitrios Kapetas, Eleni Kalogeropoulou, Panagiotis Christakakis, Christos Klaridopoulos, Eleftheria Maria Pechlivani

    Published 2025-01-01
    “…The classifier achieved an overall accuracy of 87.42% with an F1-Score of 81.13%. The per-class F1-Scores for the three classes were 85.25%, 66.67%, and 78.26%, respectively. …”
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    A Five-Level Wavelet Decomposition and Dimensional Reduction Approach for Feature Extraction and Classification of MR and CT Scan Images by Varun Srivastava, Ravindra Kumar Purwar

    Published 2017-01-01
    “…The proposed algorithm has been found better up to 3.3%, 12.75%, and 13.75% on average over the first, second, and third algorithm, respectively, using KNN and up to 6.22%, 13.9%, and 14.1% on average using ANN. …”
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    MSBKA: A Multi-Strategy Improved Black-Winged Kite Algorithm for Feature Selection of Natural Disaster Tweets Classification by Guangyu Mu, Jiaxue Li, Zhanhui Liu, Jiaxiu Dai, Jiayi Qu, Xiurong Li

    Published 2025-01-01
    “…When faced with massive text data, choosing the pivotal features, reducing the calculation expense, and increasing the model classification performance is a significant challenge. …”
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  7. 167

    Classification of benign and malignant solid breast lesions on the ultrasound images based on the textural features: the importance of the perifocal lesion area by А.А. Kolchev, D.V. Pasynkov, I.A. Egoshin, I.V. Kliouchkin, О.О. Pasynkova

    Published 2024-02-01
    “…The use of LASSO regression for feature selection enabled us to identify the most significant features for classification. Out of the 13 features selected by the LASSO method, four described the perilesional tissue, two represented the inner area of the lesion and five described the image of the gradient module. …”
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