Showing 281 - 300 results of 1,135 for search 'T13 (classification)', query time: 0.08s Refine Results
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    A New Deep Learning-Based Method for Automated Identification of Thoracic Lymph Node Stations in Endobronchial Ultrasound (EBUS): A Proof-of-Concept Study by Øyvind Ervik, Mia Rødde, Erlend Fagertun Hofstad, Ingrid Tveten, Thomas Langø, Håkon O. Leira, Tore Amundsen, Hanne Sorger

    Published 2025-01-01
    “…The model achieved an overall classification accuracy of 59.5 ± 5.2%. The highest precision, sensitivity, and F1 score were observed in station 4L, 77.6 ± 13.1%, 77.6 ± 15.4%, and 77.6 ± 15.4%, respectively. …”
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    The Fruit Recognition and Evaluation Method Based on Multi-Model Collaboration by Mingzheng Huang, Dejin Chen, Dewang Feng

    Published 2025-01-01
    “…Firstly, the detection model was used to accurately locate and crop the fruit area, and then the cropped image was input into the classification module for detailed classification. Finally, the classification results were optimized by the feature matching network. …”
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